担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

N6-methyladenine (6mA) plays a critical role in various epigenetic processing including DNA replication, DNA repair, silencing, transcription, and diseases such as cancer. To understand such epigenetic mechanisms, 6 mA has been detected by high-throughput technologies on a genome-wide scale at single-base resolution, together with conventional methods such as immunoprecipitation, mass spectrometry and capillary electrophoresis, but these experimental approaches are time-consuming and laborious. To complement these problems, we have developed a CNN-based 6 mA site predictor, named CNN6mA, which proposed two new architectures: a position-specific 1-D convolutional layer and a cross-interactive network. In the position-specific 1-D convolutional layer, position-specific filters with different window sizes were applied to an inquiry sequence instead of sharing the same filters over all positions in order to extract the position-specific features at different levels. The cross-interactive network explored the relationships between all the nucleotide patterns within the inquiry sequence. Consequently, CNN6mA outperformed the existing state-of-the-art models in many species and created the contribution score vector that intelligibly interpret the prediction mechanism. The source codes and web application in CNN6mA are freely accessible at https://github.com/kuratahiroyuki/CNN6mA.git and http://kurata35.bio.kyutech.ac.jp/CNN6mA/, respectively.

DOI： 10.1016/j.csbj.2022.12.043

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Background: Kinetic modeling is a powerful tool for understanding the dynamic behavior of biochemical systems. For kinetic modeling, determination of a number of kinetic parameters, such as the Michaelis constant (Km), is necessary, and global optimization algorithms have long been used for parameter estimation. However, the conventional global optimization approach has three problems: (i) It is computationally demanding. (ii) It often yields unrealistic parameter values because it simply seeks a better model fitting to experimentally observed behaviors. (iii) It has difficulty in identifying a unique solution because multiple parameter sets can allow a kinetic model to fit experimental data equally well (the non-identifiability problem). Results: To solve these problems, we propose the Machine Learning-Aided Global Optimization (MLAGO) method for Km estimation of kinetic modeling. First, we use a machine learning-based Km predictor based only on three factors: EC number, KEGG Compound ID, and Organism ID, then conduct a constrained global optimization-based parameter estimation by using the machine learning-predicted Km values as the reference values. The machine learning model achieved relatively good prediction scores: RMSE = 0.795 and R2 = 0.536, making the subsequent global optimization easy and practical. The MLAGO approach reduced the error between simulation and experimental data while keeping Km values close to the machine learning-predicted values. As a result, the MLAGO approach successfully estimated Km values with less computational cost than the conventional method. Moreover, the MLAGO approach uniquely estimated Km values, which were close to the measured values. Conclusions: MLAGO overcomes the major problems in parameter estimation, accelerates kinetic modeling, and thus ultimately leads to better understanding of complex cellular systems. The web application for our machine learning-based Km predictor is accessible at https://sites.google.com/view/kazuhiro-maeda/software-tools-web-apps, which helps modelers perform MLAGO on their own parameter estimation tasks.

DOI： 10.1186/s12859-022-05009-x

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記述言語：英語   掲載種別：研究論文（学術雑誌）

As one of the most prevalent post-transcriptional epigenetic modifications, N5-methylcytosine (m5C) plays an essential role in various cellular processes and disease pathogenesis. Therefore, it is important accurately identify m5C modifications in order to gain a deeper understanding of cellular processes and other possible functional mechanisms. Although a few computational methods have been proposed, their respective models have been developed using small training datasets. Hence, their practical application is quite limited in genome-wide detection. To overcome the existing limitations, we propose Deepm5C, a bioinformatics method for identifying RNA m5C sites throughout the human genome. To develop Deepm5C, we constructed a novel benchmarking dataset and investigated a mixture of three conventional feature-encoding algorithms and a feature derived from word-embedding approaches. Afterward, four variants of deep-learning classifiers and four commonly used conventional classifiers were employed and trained with the four encodings, ultimately obtaining 32 baseline models. A stacking strategy is effectively utilized by integrating the predicted output of the optimal baseline models and trained with a one-dimensional (1D) convolutional neural network. As a result, the Deepm5C predictor achieved excellent performance during cross-validation with a Matthews correlation coefficient and an accuracy of 0.697 and 0.855, respectively. The corresponding metrics during the independent test were 0.691 and 0.852, respectively. Overall, Deepm5C achieved a more accurate and stable performance than the baseline models and significantly outperformed the existing predictors, demonstrating the effectiveness of our proposed hybrid framework. Furthermore, Deepm5C is expected to assist community-wide efforts in identifying putative m5Cs and to formulate the novel testable biological hypothesis.

DOI： 10.1016/j.ymthe.2022.05.001

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担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The COVID-19 pandemic caused several million deaths worldwide. Development of anti-coronavirus drugs is thus urgent. Unlike conventional non-peptide drugs, antiviral peptide drugs are highly specific, easy to synthesize and modify, and not highly susceptible to drug resistance. To reduce the time and expense involved in screening thousands of peptides and assaying their antiviral activity, computational predictors for identifying anti-coronavirus peptides (ACVPs) are needed. However, few experimentally verified ACVP samples are available, even though a relatively large number of antiviral peptides (AVPs) have been discovered. In this study, we attempted to predict ACVPs using an AVP dataset and a small collection of ACVPs. Using conventional features, a binary profile and a word-embedding word2vec (W2V), we systematically explored five different machine learning methods: Transformer, Convolutional Neural Network, bidirectional Long Short-Term Memory, Random Forest (RF) and Support Vector Machine. Via exhaustive searches, we found that the RF classifier with W2V consistently achieved better performance on different datasets. The two main controlling factors were: (i) the dataset-specific W2V dictionary was generated from the training and independent test datasets instead of the widely used general UniProt proteome and (ii) a systematic search was conducted and determined the optimal k-mer value in W2V, which provides greater discrimination between positive and negative samples. Therefore, our proposed method, named iACVP, consistently provides better prediction performance compared with existing state-of-The-Art methods. To assist experimentalists in identifying putative ACVPs, we implemented our model as a web server accessible via the following link: http://kurata35.bio.kyutech.ac.jp/iACVP.

DOI： 10.1093/bib/bbac265

Scopus

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several experimental methods were used to identify DNA modifications. However, these experimental methods are costly and time-consuming. To detect the 6mA and complement these shortcomings of experimental methods, we proposed a novel, deep leaning approach called BERT6mA. To compare the BERT6mA with other deep learning approaches, we used the benchmark datasets including 11 species. The BERT6mA presented the highest AUCs in eight species in independent tests. Furthermore, BERT6mA showed higher and comparable performance with the state-of-the-art models while the BERT6mA showed poor performances in a few species with a small sample size. To overcome this issue, pretraining and fine-tuning between two species were applied to the BERT6mA. The pretrained and fine-tuned models on specific species presented higher performances than other models even for the species with a small sample size. In addition to the prediction, we analyzed the attention weights generated by BERT6mA to reveal how the BERT6mA model extracts critical features responsible for the 6mA prediction. To facilitate biological sciences, the BERT6mA online web server and its source codes are freely accessible at https://github.com/kuratahiroyuki/BERT6mA.git, respectively.

DOI： 10.1093/bib/bbac053

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担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.32118/ayu28009948

CiNii Research

記述言語：英語   掲載種別：研究論文（学術雑誌）

Objectives: We evaluated the time course of the American Spinal Cord Injury Association (ASIA) impairment scale (AIS) for up to three months in participants within 72 h after traumatic spinal cord injury (TSCI) with complete paralysis. We aimed to determine the most useful sacral-sparing examination (deep anal pressure [DAP], voluntary anal contraction [VAC], S4-5 light touch [LT], or pin prick [PP] sensation) in determining AIS grades. Design: Retrospective cohort study. Setting: Spinal Injuries Center, Fukuoka, Japan. Participants: Among 668 TSCI participants registered in the Japan Single Center study for Spinal Cord Injury Database (JSSCI-DB) between January 2012 and May 2020, we extracted the data of 80 patients with AIS grade A within 72 h after injury and neurological level of injury (NLI) at T12 or higher. Interventions: None. Outcome measures: The sacral-sparing examination at the time of the change to incomplete paralysis was compared to the AIS determination using a standard algorithm and with each assessment including the VAC, DAP, S4-5LT, and S4-5PP examinations at the time of AIS functional change. Agreement among assessments was evaluated using weighted kappa coefficients. The relationship was evaluated using Spearman’s rank correlation coefficients. Results: Fifteen participants (18.8%) improved to incomplete paralysis (AIS B to D) within three months after injury. The single assessment among the sacral-sparing examinations with the highest agreement and strongest correlation with AIS determination was the S4-5LT examination (k = 0.89, P < 0.01, r = 0.84, P < 0.01). Conclusions: The S4-5LT examination is key in determining complete or incomplete paralysis due to its high discriminatory power.

DOI： 10.1080/10790268.2022.2047548

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Kinetic modeling is an essential tool in systems biology research, enabling the quantitative analysis of biological systems and predicting their behavior. However, the development of kinetic models is a complex and time-consuming process. In this article, we propose a novel approach called KinModGPT, which generates kinetic models directly from natural language text. KinModGPT employs GPT as a natural language interpreter and Tellurium as an SBML generator. We demonstrate the effectiveness of KinModGPT in creating SBML kinetic models from complex natural language descriptions of biochemical reactions. KinModGPT successfully generates valid SBML models from a range of natural language model descriptions of metabolic pathways, protein–protein interaction networks, and heat shock response. This article demonstrates the potential of KinModGPT in kinetic modeling automation.

DOI： 10.3390/ijms24087296

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Drug–target protein interaction (DTI) identification is fundamental for drug discovery and drug repositioning, because therapeutic drugs act on disease-causing proteins. However, the DTI identification process often requires expensive and time-consuming tasks, including biological experiments involving large numbers of candidate compounds. Thus, a variety of computation approaches have been developed. Of the many approaches available, chemo-genomics feature-based methods have attracted considerable attention. These methods compute the feature descriptors of drugs and proteins as the input data to train machine and deep learning models to enable accurate prediction of unknown DTIs. In addition, attention-based learning methods have been proposed to identify and interpret DTI mechanisms. However, improvements are needed for enhancing prediction performance and DTI mechanism elucidation. To address these problems, we developed an attention-based method designated the interpretable cross-attention network (ICAN), which predicts DTIs using the Simplified Molecular Input Line Entry System of drugs and amino acid sequences of target proteins. We optimized the attention mechanism architecture by exploring the cross-attention or self-attention, attention layer depth, and selection of the context matrixes from the attention mechanism. We found that a plain attention mechanism that decodes drug-related protein context features without any protein-related drug context features effectively achieved high performance. The ICAN outperformed state-of-the-art methods in several metrics on the DAVIS dataset and first revealed with statistical significance that some weighted sites in the cross-attention weight matrix represent experimental binding sites, thus demonstrating the high interpretability of the results. The program is freely available at https://github.com/kuratahiroyuki/ICAN.

DOI： 10.1371/journal.pone.0276609

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担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：記事・総説・解説・論説等（学術雑誌）

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies espe-cially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we dis-cuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

DOI： 10.2174/0929867328666210804090224

Scopus

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Viral infections represent a major health concern worldwide. The alarming rate at which SARS-CoV-2 spreads, for example, led to a worldwide pandemic. Viruses incorporate genetic material into the host genome to hijack host cell functions such as the cell cycle and apoptosis. In these viral processes, protein–protein interactions (PPIs) play critical roles. Therefore, the identification of PPIs between humans and viruses is crucial for understanding the infection mechanism and host immune responses to viral infections and for discovering effective drugs. Experimental methods including mass spectrometry-based proteomics and yeast two-hybrid assays are widely used to identify human-virus PPIs, but these experimental methods are time-consuming, expensive, and laborious. To overcome this problem, we developed a novel computational predictor, named cross-attention PHV, by implementing two key technologies of the cross-attention mechanism and a one-dimensional convolutional neural network (1D-CNN). The cross-attention mechanisms were very effective in enhancing prediction and generalization abilities. Application of 1D-CNN to the word2vec-generated feature matrices reduced computational costs, thus extending the allowable length of protein sequences to 9000 amino acid residues. Cross-attention PHV outperformed existing state-of-the-art models using a benchmark dataset and accurately predicted PPIs for unknown viruses. Cross-attention PHV also predicted human–SARS-CoV-2 PPIs with area under the curve values >0.95. The Cross-attention PHV web server and source codes are freely available at https://kurata35.bio.kyutech.ac.jp/Cross-attention_PHV/ and https://github.com/kuratahiroyuki/Cross-Attention_PHV, respectively.

DOI： 10.1016/j.csbj.2022.10.012

Scopus

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Viral infection involves a large number of protein-protein interactions (PPIs) between human and virus. The PPIs range from the initial binding of viral coat proteins to host membrane receptors to the hijacking of host transcription machinery. However, few interspecies PPIs have been identified, because experimental methods including mass spectrometry are time-consuming and expensive, and molecular dynamic simulation is limited only to the proteins whose 3D structures are solved. Sequence-based machine learning methods are expected to overcome these problems. We have first developed the LSTM model with word2vec to predict PPIs between human and virus, named LSTM-PHV, by using amino acid sequences alone. The LSTM-PHV effectively learnt the training data with a highly imbalanced ratio of positive to negative samples and achieved AUCs of 0.976 and 0.973 and accuracies of 0.984 and 0.985 on the training and independent datasets, respectively. In predicting PPIs between human and unknown or new virus, the LSTM-PHV learned greatly outperformed the existing state-of-the-art PPI predictors. Interestingly, learning of only sequence contexts as words is sufficient for PPI prediction. Use of uniform manifold approximation and projection demonstrated that the LSTM-PHV clearly distinguished the positive PPI samples from the negative ones. We presented the LSTM-PHV online web server and support data that are freely available at http://kurata35.bio.kyutech.ac.jp/LSTM-PHV.

DOI： 10.1093/bib/bbab228

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Neuropeptides (NPs) are the most versatile neurotransmitters in the immune systems that regulate various central anxious hormones. An efficient and effective bioinformatics tool for rapid and accurate large-scale identification of NPs is critical in immunoinformatics, which is indispensable for basic research and drug development. Although a few NP prediction tools have been developed, it is mandatory to improve their NPs' prediction performances. In this study, we have developed a machine learning-based meta-predictor called NeuroPred-FRL by employing the feature representation learning approach. First, we generated 66 optimal baseline models by employing 11 different encodings, six different classifiers and a two-step feature selection approach. The predicted probability scores of NPs based on the 66 baseline models were combined to be deemed as the input feature vector. Second, in order to enhance the feature representation ability, we applied the two-step feature selection approach to optimize the 66-D probability feature vector and then inputted the optimal one into a random forest classifier for the final meta-model (NeuroPred-FRL) construction. Benchmarking experiments based on both cross-validation and independent tests indicate that the NeuroPred-FRL achieves a superior prediction performance of NPs compared with the other state-of-the-art predictors. We believe that the proposed NeuroPred-FRL can serve as a powerful tool for large-scale identification of NPs, facilitating the characterization of their functional mechanisms and expediting their applications in clinical therapy. Moreover, we interpreted some model mechanisms of NeuroPred-FRL by leveraging the robust SHapley Additive exPlanation algorithm.

DOI： 10.1093/bib/bbab167

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Methylation of DNA N6-methyladenosine (6mA) is a type of epigenetic modification that plays pivotal roles in various biological processes. The accurate genome-wide identification of 6mA is a challenging task that leads to understanding the biological functions. For the last 5 years, a number of bioinformatics approaches and tools for 6mA site prediction have been established, and some of them are easily accessible as web application. Nevertheless, the accurate genome-wide identification of 6mA is still one of the challenging works that lead to understanding the biological functions. Especially in practical applications, these tools have implemented diverse encoding schemes, machine learning algorithms and feature selection methods, whereas few systematic performance comparisons of 6mA site predictors have been reported. In this review, 11 publicly available 6mA predictors evaluated with seven different species-specific datasets (Arabidopsis thaliana, Tolypocladium, Diospyros lotus, Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans and Escherichia coli). Of those, few species are close homologs, and the remaining datasets are distant sequences. Our independent, validation tests demonstrated that Meta-i6mA and MM-6mAPred models for A. thaliana, Tolypocladium, S. cerevisiae and D. melanogaster achieved excellent overall performance when compared with their counterparts. However, none of the existing methods were suitable for E. coli, C. elegans and D. lotus. A feasibility of the existing predictors is also discussed for the seven species. Our evaluation provides useful guidelines for the development of 6mA site predictors and helps biologists selecting suitable prediction tools.

DOI： 10.1093/bfgp/elaa028

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DNA N6-methyladenine (6mA) represents important epigenetic modifications, which are responsible for various cellular processes. The accurate identification of 6mA sites is one of the challenging tasks in genome analysis, which leads to an understanding of their biological functions. To date, several species-specific machine learning (ML)-based models have been proposed, but majority of them did not test their model to other species. Hence, their practical application to other plant species is quite limited. In this study, we explored 10 different feature encoding schemes, with the goal of capturing key characteristics around 6mA sites. We selected five feature encoding schemes based on physicochemical and position-specific information that possesses high discriminative capability. The resultant feature sets were inputted to six commonly used ML methods (random forest, support vector machine, extremely randomized tree, logistic regression, naïve Bayes and AdaBoost). The Rosaceae genome was employed to train the above classifiers, which generated 30 baseline models. To integrate their individual strength, Meta-i6mA was proposed that combined the baseline models using the meta-predictor approach. In extensive independent test, Meta-i6mA showed high Matthews correlation coefficient values of 0.918, 0.827 and 0.635 on Rosaceae, rice and Arabidopsis thaliana, respectively and outperformed the existing predictors. We anticipate that the Meta-i6mA can be applied across different plant species. Furthermore, we developed an online user-friendly web server, which is available at http://kurata14.bio.kyutech.ac.jp/Meta-i6mA/.

DOI： 10.1093/bib/bbaa202

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyro-sine is a prerequisite to understanding the molecular function of nitrated proteins. Thanks to the progress of machine learning, computational prediction can play a vital role before the biological experimentation. Herein, we developed a computational predictor PredNTS by integrating multiple sequence features including K-mer, composition of k-spaced amino acid pairs (CKSAAP), AAindex, and binary encoding schemes. The important features were selected by the recursive feature elimination approach using a random forest classifier. Finally, we linearly combined the successive random forest (RF) probability scores generated by the different, single encoding-employing RF models. The resultant PredNTS predictor achieved an area under a curve (AUC) of 0.910 using five-fold cross validation. It outperformed the existing predictors on a comprehensive and independent dataset. Furthermore, we investigated several machine learning algorithms to demonstrate the superiority of the employed RF algorithm. The PredNTS is a useful computational resource for the prediction of nitrotyrosine sites. The web-application with the curated datasets of the PredNTS is publicly available.

DOI： 10.3390/ijms22052704

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Redox-sensitive cysteine (RSC) thiol contributes to many biological processes. The identification of RSC plays an important role in clarifying some mechanisms of redox-sensitive factors; nonetheless, experimental investigation of RSCs is expensive and time-consuming. The computational approaches that quickly and accurately identify candidate RSCs using the sequence information are urgently needed. Herein, an improved and robust computational predictor named IRC-Fuse was developed to identify the RSC by fusing of multiple feature representations. To enhance the performance of our model, we integrated the probability scores evaluated by the random forest models implementing different encoding schemes. Cross-validation results exhibited that the IRC-Fuse achieved accuracy and AUC of 0.741 and 0.807, respectively. The IRC-Fuse outperformed exiting methods with improvement of 10% and 13% on accuracy and MCC, respectively, over independent test data. Comparative analysis suggested that the IRC-Fuse was more effective and promising than the existing predictors. For the convenience of experimental scientists, the IRC-Fuse online web server was implemented and publicly accessible at http://kurata14.bio.kyutech.ac.jp/IRC-Fuse/.

DOI： 10.1007/s10822-020-00368-0

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Biological Sciences; Endocrinology; Mathematical Biosciences; Metabolomics; Systems Biology

DOI： 10.1016/j.isci.2021.102101

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Pupylation is a type of reversible post-translational modification of proteins, which plays a key role in the cellular function of microbial organisms. Several proteomics methods have been developed for the prediction and analysis of pupylated proteins and pupylation sites. However, the traditional experimental methods are laborious and time-consuming. Hence, computational algorithms are highly needed that can predict potential pupylation sites using sequence features. In this research, a new prediction model, PUP-Fuse, has been developed for pupylation site prediction by integrating multiple sequence representations. Meanwhile, we explored the five types of feature encoding approaches and three machine learning (ML) algorithms. In the final model, we integrated the successive ML scores using a linear regression model. The PUP-Fuse achieved a Mathew correlation value of 0.768 by a 10-fold cross-validation test. It also outperformed existing predictors in an independent test. The web server of the PUP-Fuse with curated datasets is freely available.

DOI： 10.3390/ijms22042120

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Linear B-cell epitopes are critically important for immunological applications, such as vaccine design, immunodiagnostic test, and antibody production, as well as disease diagnosis and therapy. The accurate identification of linear B-cell epitopes remains challenging despite several decades of research. In this work, we have developed a novel predictor, Identification of B-Cell Epitope (iLBE), by integrating evolutionary and sequence-based features. The successive feature vectors were optimized by a Wilcoxon-rank sum test. Then the random forest (RF) algorithm using the optimal consecutive feature vectors was applied to predict linear B-cell epitopes. We combined the RF scores by the logistic regression to enhance the prediction accuracy. iLBE yielded an area under curve score of 0.809 on the training dataset and outperformed other prediction models on a comprehensive independent dataset. iLBE is a powerful computational tool to identify the linear B-cell epitopes and would help to develop penetrating diagnostic tests. A web application with curated datasets for iLBE is freely accessible at http://kurata14.bio.kyutech.ac.jp/iLBE/.

DOI： 10.1016/j.gpb.2019.04.004

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Inside living cells, proteins or mRNA can show oscillations even without a periodic driving force. Such genetic oscillations are precise timekeepers for cell-cycle regulations, pattern formation during embryonic development in higher animals, and daily cycle maintenance in most organisms. The synchronization between oscillations in adjacent cells happens via intercellular coupling, which is essential for periodic segmentation formation in vertebrates and other biological processes. While molecular mechanisms of generating sustained oscillations are quite well understood, how do simple intercellular coupling produces robust synchronizations are still poorly understood? To address this question, we investigate two models of coupled gene oscillators - activator-based coupled oscillators (ACO) and repressor-based coupled oscillators (RCO) models. In our study, a single autonomous oscillator (that operates in a single cell) is based on a negative feedback, which is delayed by intracellular dynamics of an intermediate species. For the ACO model (RCO), the repressor protein of one cell activates (represses) the production of another protein in the neighbouring cell after a intercellular time delay. We investigate the coupled models in the presence of intrinsic noise due to the inherent stochasticity of the biochemical reactions. We analyze the collective oscillations from stochastic trajectories in the presence and absence of explicit coupling delay and make careful comparison between two models. Our results show no clear synchronizations in the ACO model when the coupling time delay is zero. However, a non-zero coupling delay can lead to anti-phase synchronizations in ACO. Interestingly, the RCO model shows robust in-phase synchronizations in the presence and absence of the coupling time delay. Our results suggest that the naturally occurring intercellular couplings might be based on repression rather than activation where in-phase synchronization is crucial.

DOI： 10.1016/j.ifacol.2021.10.318

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Kinetic modeling is essential for understanding the dynamic behavior of biochemical networks, such as metabolic and signal transduction pathways. However, parameter estimation remains a major bottleneck in kinetic modeling. Although several software tools have been developed to address this issue, they are meant to be used by experts, and their lack of user-friendliness hampers their general usage by capable yet inexperienced scientists. One of the difficulties is the lack of graphical user interfaces (GUIs), which means that users must learn how to write scripts for parameter estimation. In this study, we present RCGAToolbox, a user-friendly parameter estimation software that provides real-coded genetic algorithms (RCGAs). The RCGAToolbox has two RCGAs: the unimodal normal distribution crossover with minimal generation gap (UNDX/MGG) and the real-coded ensemble crossover star with just generation gap (REXstar/JGG). To facilitate parameter estimation, RCGAToolbox offers straightforward access to powerful RCGAs, such as GUIs, an easy-to-use installer, and a comprehensive user guide. Moreover, the RCGAToolbox supports systems biology standards for better usability and interoperability. The RCGAToolbox is available at https://github.com/kmaeda16/RCGAToolbox under GNU GPLv3, along with the user guide and application examples. The RCGAToolbox runs on MATLAB (R2016a or later) in Windows, Linux, and Mac.

DOI： 10.2197/IPSJTBIO.14.30

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

<p>Kinetic modeling is essential for understanding the dynamic behavior of biochemical networks, such as metabolic and signal transduction pathways. However, parameter estimation remains a major bottleneck in kinetic modeling. Although several software tools have been developed to address this issue, they are meant to be used by experts, and their lack of user-friendliness hampers their general usage by capable yet inexperienced scientists. One of the difficulties is the lack of graphical user interfaces (GUIs), which means that users must learn how to write scripts for parameter estimation. In this study, we present RCGAToolbox, a user-friendly parameter estimation software that provides real-coded genetic algorithms (RCGAs). The RCGAToolbox has two RCGAs: the unimodal normal distribution crossover with minimal generation gap (UNDX/MGG) and the real-coded ensemble crossover star with just generation gap (REX^star/JGG). To facilitate parameter estimation, RCGAToolbox offers straightforward access to powerful RCGAs, such as GUIs, an easy-to-use installer, and a comprehensive user guide. Moreover, the RCGAToolbox supports systems biology standards for better usability and interoperability. The RCGAToolbox is available at https://github.com/kmaeda16/RCGAToolbox under GNU GPLv3, along with the user guide and application examples. The RCGAToolbox runs on MATLAB (R2016a or later) in Windows, Linux, and Mac.</p>

DOI： 10.2197/ipsjtbio.14.30

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130008120842

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Circadian rhythms (approx. 24 h) show the robustness of key oscillatory features such as phase, period and amplitude against external and internal variations. The robustness of Drosophila circadian clocks can be generated by interlocked transcriptional-translational feedback loops, where two negative feedback loops are coupled through mutual activations. The mechanisms by which such coupling protocols have survived out of many possible protocols remain to be revealed. To address this question, we investigated two distinct coupling protocols: activator-coupled oscillators (ACO) and repressor-coupled oscillators (RCO). We focused on the two coupling parameters: coupling dissociation constant and coupling time-delay. Interestingly, the ACO was able to produce anti-phase or morning-evening cycles, whereas the RCO produced in-phase ones. Deterministic and stochastic analyses demonstrated that the anti-phase ACO provided greater fluctuations in amplitude not only with respect to changes in coupling parameters but also to random parameter perturbations than the in-phase RCO. Moreover, the ACO deteriorated the entrainability to the day-night master clock, whereas the RCO produced high entrainability. Considering that the real, interlocked feedback loops have evolved as the ACO, instead of the RCO, we first proposed a hypothesis that the morning-evening or anti-phase cycle is more essential for Drosophila than achieving robustness and entrainability.

DOI： 10.1098/rsif.2020.0287

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© Copyright © 2020 Matsuoka and Kurata. Lignocellulosic biomass can be hydrolyzed into two major sugars of glucose and xylose, and thus the strategy for the efficient consumption of both sugars is highly desirable. NADPH is the essential molecule for the production of industrially important value-added chemicals, and thus its availability is quite important. Escherichia coli mutant lacking the pgi gene encoding phosphoglucose isomerase (Pgi) has been preferentially used to overproduce the NADPH. However, there exists a disadvantage that the cell growth rate becomes low for the mutant grown on glucose. This limits the efficient NADPH production, and therefore, it is quite important to investigate how addition of different carbon source such as xylose (other than glucose) effectively improves the NADPH production. In this study, we have developed a kinetic model to propose an efficient NADPH production system using E. coli pgi-knockout mutant with a mixture of glucose and xylose. The proposed system adds xylose to glucose medium to recover the suppressed growth of the pgi mutant, and determines the xylose content to maximize the NADPH productivity. Finally, we have designed a mevalonate (MVA) production system by implementing ArcA overexpression into the pgi-knockout mutant using a mixture of glucose and xylose. In addition to NADPH overproduction, the accumulation of acetyl-CoA (AcCoA) is necessary for the efficient MVA production. In the present study, therefore, we considered to overexpress ArcA, where ArcA overexpression suppresses the TCA cycle, causing the overflow of AcCoA, a precursor of MVA. We predicted the xylose content that maximizes the MVA production. This approach demonstrates the possibility of a great progress in the computer-aided rational design of the microbial cell factories for useful metabolite production.

DOI： 10.3389/fbioe.2020.00277

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：記事・総説・解説・論説等（学術雑誌）

© 2020 Bentham Science Publishers. A variety of protein post-translational modifications has been identified that control many cellular functions. Phosphorylation studies in mycobacterial organisms have shown critical importance in diverse biological processes, such as intercellular communication and cell division. Recent technical advances in high-precision mass spectrometry have determined a large number of microbial phosphorylated proteins and phosphorylation sites throughout the proteome analysis. Identification of phosphorylated proteins with specific modified residues through experimentation is often labor-intensive, costly and time-consuming. All these limitations could be overcome through the application of machine learning (ML) approaches. However, only a limited number of computational phosphory-lation site prediction tools have been developed so far. This work aims to present a complete survey of the existing ML-predictors for microbial phosphorylation. We cover a variety of important aspects for developing a successful predictor, including operating ML algorithms, feature selection methods, win-dow size, and software utility. Initially, we review the currently available phosphorylation site data-bases of the microbiome, the state-of-the-art ML approaches, working principles, and their perfor-mances. Lastly, we discuss the limitations and future directions of the computational ML methods for the prediction of phosphorylation.

DOI： 10.2174/1389202921666200427210833

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020 The Authors N4-methylcytosine (4mC) is one of the most important DNA modifications and involved in regulating cell differentiations and gene expressions. The accurate identification of 4mC sites is necessary to understand various biological functions. In this work, we developed a new computational predictor called i4mC-Mouse to identify 4mC sites in the mouse genome. Herein, six encoding schemes of k-space nucleotide composition (KSNC), k-mer nucleotide composition (Kmer), mono nucleotide binary encoding (MBE), dinucleotide binary encoding, electron–ion interaction pseudo potentials (EIIP) and dinucleotide physicochemical composition were explored that cover different characteristics of DNA sequence information. Subsequently, we built six RF-based encoding models and then linearly combined their probability scores to construct the final predictor. Among the six RF-based models, the Kmer, KSNC, MBE, and EIIP encodings are sufficient, which contributed to 10%, 45%, 25%, and 20% of the prediction performance, respectively. On the independent test the i4mC-Mouse predicted the 4mC sites with accuracy and MCC of 0.816 and 0.633, respectively, which were approximately 2.5% and 5% higher than those of the existing method (4mCpred-EL). For experimental biologists, a freely available web application was implemented at http://kurata14.bio.kyutech.ac.jp/i4mC-Mouse/.

DOI： 10.1016/j.csbj.2020.04.001

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020, The Author(s), under exclusive licence to International Spinal Cord Society. Study design: Retrospective statistical analysis of database. Objectives: Prediction of the Spinal Cord Independence Measure version III Total Score (SCIM-TS) at 6 months after injury based on physical findings at 1 month after injury is an important index for rehabilitation approach in the recovery phase. Setting: Spinal Injuries Center, Fukuoka, Japan. Methods: The study participants were selected from patients with traumatic spinal cord injuries who were registered in the Japan Single Center Study for Spinal Cord Injury Data Base (JSSCI-DB) of the Japan Spinal Injuries Center specializing in spine and spinal cord injuries. Of the 534 participants registered with the JSSCI-DB between January 2012 and October 2018, we retrospectively extracted 137 participants for 6 months after injury, and these participants were included in this study. Results: According to multiple regression analysis, SCIM-TS at 6 months after injury could be predicted based on only six variables, i.e., age at injury, three key muscles (C6 wrist extensors, C8 finger flexors, and L3 knee extensors), and two mobility assessments (WISCI and SCIM−item13) (Adjusted R-Squared: 0.83). These six independent variables were significant factors reflecting SCIM-TS at 6 months. Conclusions: In rehabilitation after traumatic spinal cord injuries, a simple and reliable prognostic model can help accurately predict the achievable activity of daily living competency to set a goal. In addition, if the procedure is simple, evaluation can be completed in a short period of time, and the physical burden on both treating staff and patients can be reduced.

DOI： 10.1038/s41393-020-0488-5

Scopus

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：日本語   掲載種別：記事・総説・解説・論説等（学術雑誌）

CiNii Research

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020, Springer Nature B.V. DNA N6-methyladenine (6 mA) is one of the most vital epigenetic modifications and involved in controlling the various gene expression levels. With the avalanche of DNA sequences generated in numerous databases, the accurate identification of 6 mA plays an essential role for understanding molecular mechanisms. Because the experimental approaches are time-consuming and costly, it is desirable to develop a computation model for rapidly and accurately identifying 6 mA. To the best of our knowledge, we first proposed a computational model named i6mA-Fuse to predict 6 mA sites from the Rosaceae genomes, especially in Rosa chinensis and Fragaria vesca. We implemented the five encoding schemes, i.e., mononucleotide binary, dinucleotide binary, k-space spectral nucleotide, k-mer, and electron–ion interaction pseudo potential compositions, to build the five, single-encoding random forest (RF) models. The i6mA-Fuse uses a linear regression model to combine the predicted probability scores of the five, single encoding-based RF models. The resultant species-specific i6mA-Fuse achieved remarkably high performances with AUCs of 0.982 and 0.978 and with MCCs of 0.869 and 0.858 on the independent datasets of Rosa chinensis and Fragaria vesca, respectively. In the F. vesca-specific i6mA-Fuse, the MBE and EIIP contributed to 75% and 25% of the total prediction; in the R. chinensis-specific i6mA-Fuse, Kmer, MBE, and EIIP contribute to 15%, 65%, and 20% of the total prediction. To assist high-throughput prediction for DNA 6 mA identification, the i6mA-Fuse is publicly accessible at https://kurata14.bio.kyutech.ac.jp/i6mA-Fuse/.

DOI： 10.1007/s11103-020-00988-y

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担当区分：責任著者   記述言語：英語   掲載種別：記事・総説・解説・論説等（学術雑誌）

© 2020 Bentham Science Publishers. Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.

DOI： 10.2174/1389202921999200625103936

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020, Springer Nature Switzerland AG. A proinflammatory peptide (PIP) is a type of signaling molecules that are secreted from immune cells, which contributes to the first line of defense against invading pathogens. Numerous experiments have shown that PIPs play an important role in human physiology such as vaccines and immunotherapeutic drugs. Considering high-throughput laboratory methods that are time consuming and costly, effective computational methods are great demand to timely and accurately identify PIPs. Thus, in this study, we proposed a computational model in conjunction with a multiple feature representation, called ProIn-Fuse, to improve the performance of PIPs identification. Specifically, a feature representation learning model was utilized to generate the probabilistic scores by using the random forest models employing eight sequence encoding schemes. Finally, the ProIn-Fuse was constructed by linearly combining the resultant eight probabilistic scores. Evaluated through independent test, the ProIn-Fuse yielded an accuracy of 0.746, which was 10% higher than those obtained by the state-of-the-art PIP predictors. The proposed ProIn-Fuse can facilitate faster and broader applications of PIPs in drug design and development. The web server, datasets and online instruction are freely accessible at http://kurata14.bio.kyutech.ac.jp/ProIn-Fuse.

DOI： 10.1007/s10822-020-00343-9

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019 The Author(s). Background: Cellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network. Results: We find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory. Conclusions: Our work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity when designing synthetic circuits with memory function.

DOI： 10.1186/s12859-019-3315-2

Kyutacar

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019, The Author(s). Protein phosphorylation on serine (S) and threonine (T) has emerged as a key device in the control of many biological processes. Recently phosphorylation in microbial organisms has attracted much attention for its critical roles in various cellular processes such as cell growth and cell division. Here a novel machine learning predictor, MPSite (Microbial Phosphorylation Site predictor), was developed to identify microbial phosphorylation sites using the enhanced characteristics of sequence features. The final feature vectors optimized via a Wilcoxon rank sum test. A random forest classifier was then trained using the optimum features to build the predictor. Benchmarking investigation using the 5-fold cross-validation and independent datasets test showed that the MPSite is able to achieve robust performance on the S- and T-phosphorylation site prediction. It also outperformed other existing methods on the comprehensive independent datasets. We anticipate that the MPSite is a powerful tool for proteome-wide prediction of microbial phosphorylation sites and facilitates hypothesis-driven functional interrogation of phosphorylation proteins. A web application with the curated datasets is freely available at http://kurata14.bio.kyutech.ac.jp/MPSite/.

DOI： 10.1038/s41598-019-44548-x

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019, The Author(s). Many metabolic cycles, including the tricarboxylic acid cycle, glyoxylate cycle, Calvin cycle, urea cycle, coenzyme recycling, and substrate cycles, are well known to catabolize and anabolize different metabolites for efficient energy and mass conversion. In terms of stoichiometric structure, this study explicitly identifies two types of metabolic cycles. One is the well-known, elementary cycle that converts multiple substrates into different products and recycles one of the products as a substrate, where the recycled substrate is supplied from the outside to run the cycle. The other is the self-replenishment cycle that merges multiple substrates into two or multiple identical products and reuses one of the products as a substrate. The substrates are autonomously supplied within the cycle. This study first defines the self-replenishment cycles that many scientists have overlooked despite its functional importance. Theoretical analysis has revealed the design principle of the self-replenishment cycle that presents a threshold response without any bistability nor cooperativity. To verify the principle, three detailed kinetic models of self-replenishment cycles embedded in an E. coli metabolic system were simulated. They presented the threshold response or digital switch-like function that steeply shift metabolic status.

DOI： 10.1038/s41598-019-53589-1

Kyutacar

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019, The Author(s). The complex ammonium transport and assimilation network of E. coli involves the ammonium transporter AmtB, the regulatory proteins GlnK and GlnB, and the central N-assimilating enzymes together with their highly complex interactions. The engineering and modelling of such a complex network seem impossible because functioning depends critically on a gamut of data known at patchy accuracy. We developed a way out of this predicament, which employs: (i) a constrained optimization-based technology for the simultaneous fitting of models to heterogeneous experimental data sets gathered through diverse experimental set-ups, (ii) a ‘rubber band method’ to deal with different degrees of uncertainty, both in experimentally determined or estimated parameter values and in measured transient or steady-state variables (training data sets), (iii) integration of human expertise to decide on accuracies of both parameters and variables, (iv) massive computation employing a fast algorithm and a supercomputer, (v) an objective way of quantifying the plausibility of models, which makes it possible to decide which model is the best and how much better that model is than the others. We applied the new technology to the ammonium transport and assimilation network, integrating recent and older data of various accuracies, from different expert laboratories. The kinetic model objectively ranked best, has E. coli's AmtB as an active transporter of ammonia to be assimilated with GlnK minimizing the futile cycling that is an inevitable consequence of intracellular ammonium accumulation. It is 130 times better than a model with facilitated passive transport of ammonia.

DOI： 10.1038/s41540-019-0091-6

Kyutacar

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019 Federation of European Biochemical Societies Tuberculosis (TB) is a leading killer caused by Mycobacterium tuberculosis. Recently, anti-TB peptides have provided an alternative approach to combat antibiotic tolerance. We have developed an effective computational predictor, identification of antitubercular peptides (iAntiTB), by the integration of multiple feature vectors deriving from the amino acid sequences via random forest (RF) and support vector machine (SVM) classifiers. The iAntiTB combines the RF and SVM scores via linear regression to enhance the prediction accuracy. To make a robust and accurate predictor, we prepared the two datasets with different types of negative samples. The iAntiTB achieved area under the ROC curve values of 0.896 and 0.946 on the training datasets of the first and second datasets, respectively. The iAntiTB outperformed the other existing predictors.

DOI： 10.1002/1873-3468.13536

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：記事・総説・解説・論説等（学術雑誌）

Lysine succinylation is a form of posttranslational modification of the proteins that play an essential functional role in every aspect of cell metabolism in both prokaryotes and eukaryotes. Aside from experimental identification of succinylation sites, there has been an intense effort geared towards the development of sequence-based prediction through machine learning, due to its promising and essential properties of being highly accurate, robust and cost-effective. In spite of these advantages, there are several problems that are in need of attention in the design and development of succinylation site predictors. Notwithstanding of many studies on the employment of machine learning approaches, few articles have examined this bioinformatics field in a systematic manner. Thus, we review the advancements regarding the current state-of-the-art prediction models, datasets, and online resources and illustrate the challenges and limitations to present a useful guideline for developing powerful succinylation site prediction tools.

DOI： 10.3390/cells8020095

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019 Khatun, Hasan and Kurata. Numerous inflammatory diseases and autoimmune disorders by therapeutic peptides have received substantial consideration; however, the exploration of anti-inflammatory peptides via biological experiments is often a time-consuming and expensive task. The development of novel in silico predictors is desired to classify potential anti-inflammatory peptides prior to in vitro investigation. Herein, an accurate predictor, called PreAIP (Predictor of Anti-Inflammatory Peptides) was developed by integrating multiple complementary features. We systematically investigated different types of features including primary sequence, evolutionary and structural information through a random forest classifier. The final PreAIP model achieved an AUC value of 0.833 in the training dataset via 10-fold cross-validation test, which was better than that of existing models. Moreover, we assessed the performance of the PreAIP with an AUC value of 0.840 on a test dataset to demonstrate that the proposed method outperformed the two existing methods. These results indicated that the PreAIP is an accurate predictor for identifying AIPs and contributes to the development of AIPs therapeutics and biomedical research. The curated datasets and the PreAIP are freely available at http://kurata14.bio.kyutech.ac.jp/PreAIP/.

DOI： 10.3389/fgene.2019.00129

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 Elsevier B.V. One of the most important epigenetic modifications is N4-methylcytosine, which regulates many biological processes including DNA replication and chromosome stability. Identification of N4-methylcytosine sites is pivotal to understand specific biological functions. Herein, we developed the first bioinformatics tool called i4mC-ROSE for identifying N4-methylcytosine sites in the genomes of Fragaria vesca and Rosa chinensis in the Rosaceae, which utilizes a random forest classifier with six encoding methods that cover various aspects of DNA sequence information. The i4mC-ROSE predictor achieves area under the curve scores of 0.883 and 0.889 for the two genomes during cross-validation. Moreover, the i4mC-ROSE outperforms other classifiers tested in this study when objectively evaluated on the independent datasets. The proposed i4mC-ROSE tool can serve users' demand for the prediction of 4mC sites in the Rosaceae genome. The i4mC-ROSE predictor and utilized datasets are publicly accessible at http://kurata14.bio.kyutech.ac.jp/i4mC-ROSE/.

DOI： 10.1016/j.ijbiomac.2019.12.009

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2019 The Royal Society of Chemistry. Cysteine S-nitrosylation is a type of reversible post-translational modification of proteins, which controls diverse biological processes. It is associated with redox-based cellular signaling to protect against oxidative stress. The identification of S-nitrosylation sites is an important step to reveal the function of proteins; however, experimental identification of S-nitrosylation is expensive and time-consuming work. Hence, sequence-based computational prediction of potential S-nitrosylation sites is highly sought before experimentation. Herein, a novel predictor PreSNO has been developed that integrates multiple encoding schemes by the support vector machine and random forest algorithms. The PreSNO achieved an accuracy and Matthews correlation coefficient value of 0.752 and 0.252 respectively in classifying between SNO and non-SNO sites when evaluated on the independent dataset, outperforming the existing methods. The web application of the PreSNO and its associated datasets are freely available at http://kurata14.bio.kyutech.ac.jp/PreSNO/.

DOI： 10.1039/c9mo00098d

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. Zea mays (maize) is one of the most vital crops which are grown widely in the world. To understand the molecular structures and functions of maize, the identification of protein-protein interaction (PPI) is very important. PPI identification by wet lab experiments is time-consuming, expensive and laborious. These days in silico methods that accurately predict potential PPIs based on protein sequence information are highly demanded. Research on PPI prediction in maize is currently very limited, and no dedicated bioinformatics schemes are available. In this work, we proposed a novel approach, termed SIPMA (Systematic Identification of PPI in Maize using Autocorrelation). A machine learning random forest classifier was trained with autocorrelation features to build the prediction model. The SIPMA, which was tested by the experimentally verified PPI dataset of maize, yielded a prediction accuracy of 0.899 when the specificity was 0.969 on the training set. The SIPMA achieved promising performances on the test datasets. Compared with different sequence-based encoding and statistical learning methods, the SIPMA was a powerful computational resource for identifying PPIs in maize.

DOI： 10.1109/BIBE.2018.00030

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. Lysine malonylation is a newly discovered post-translational modification of proteins, which plays an important role in regulating many cellular fonctions. Several approaches are available to identify malonylation proteins and its malonylation sites, however; experimental identification of malonylation sites is often laborious and costly. Therefore, computational schemes are needed to identify potential malonylation sites prior to in vitro experimentation. In this paper, a novel computational scheme iLMS (Identification of Lysine-Malonylation Sites) has been developed by combining primary sequences and evolutionary features via a support vector machine classifier. The final iLMS scheme achieved a robust performance in cross-validation test in both human and mouse datasets. For the mouse data, the iLMS predictor outperformed other existing implementations. The iLMS is a promising computational scheme for the prediction of malonylation sites.

DOI： 10.1109/BIBE.2018.00077

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 Hasan, Kurata. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Lysine succinylation is one of the dominant post-translational modification of the protein that contributes to many biological processes including cell cycle, growth and signal transduction pathways. Identification of succinylation sites is an important step for understanding the function of proteins. The complicated sequence patterns of protein succinylation revealed by proteomic studies highlight the necessity of developing effective species-specific in silico strategies for global prediction succinylation sites. Here we have developed the generic and nine speciesspecific succinylation site classifiers through aggregating multiple complementary features. We optimized the consecutive features using the Wilcoxon-rank feature selection scheme. The final feature vectors were trained by a random forest (RF) classifier. With an integration of RF scores via logistic regression, the resulting predictor termed GPSuc achieved better performance than other existing generic and species-specific succinylation site predictors. To reveal the mechanism of succinylation and assist hypothesis-driven experimental design, our predictor serves as a valuable resource. To provide a promising performance in large-scale datasets, a web application was developed at http://kurata14.bio.kyutech.ac.jp/GPSuc/.

DOI： 10.1371/journal.pone.0200283

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記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.4172/2332-0737.1000137

記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.18632/oncoscience.411

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 Elsevier Ltd Oscillatory phenomena play a major role in organisms. In some biological oscillations such as cell cycles and heartbeats, the period can be tuned without significant changes in the amplitude. This property is called (period) tunability, one of the prominent features of biological oscillations. However, how biological oscillators produce tunable oscillations remains largely unexplored. We tackle this question using computational experiments. It has been reported that positive-plus-negative feedback oscillators produce tunable oscillations through the hysteresis-based mechanism. First, in this study, we confirmed that positive-plus-negative feedback oscillators generate tunable oscillations. Second, we found that tunability is positively correlated with the dynamic range of oscillations. Third, we showed that long negative feedback oscillators without any additional positive feedback loops can produce tunable oscillations. Finally, we computationally demonstrated that by lengthening the negative feedback loop, the Repressilator, known as a non-tunable synthetic gene oscillator, can be converted into a tunable oscillator. This work provides synthetic biologists with clues to design tunable gene oscillators.

DOI： 10.1016/j.jtbi.2017.12.014

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 The Society for Biotechnology, Japan Many kinetic models of Escherichia coli central metabolism have been built, but few models accurately reproduced the dynamic behaviors of wild type and multiple genetic mutants. In 2016, our latest kinetic model improved problems of existing models to reproduce the cell growth and glucose uptake of wild type, ΔpykA:pykF and Δpgi in a batch culture, while it overestimated the glucose uptake and cell growth rates of Δppc and hardly captured the typical characteristics of the glyoxylate and TCA cycle fluxes for Δpgi and Δppc. Such discrepancies between the simulated and experimental data suggested biological complexity. In this study, we overcame these problems by assuming critical mechanisms regarding the OAA-regulated isocitrate dehydrogenase activity, aceBAK gene regulation and growth suppression. The present model accurately predicts the extracellular and intracellular dynamics of wild type and many gene knockout mutants in batch and continuous cultures. It is now the most accurate, detailed kinetic model of E. coli central carbon metabolism and will contribute to advances in mathematical modeling of cell factories.

DOI： 10.1016/j.jbiosc.2017.09.005

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

<p>Kinetic modeling is a powerful tool to understand how a biochemical system behaves as a whole. To develop a realistic and predictive model, kinetic parameters need to be estimated so that a model fits experimental data. However, parameter estimation remains a major bottleneck in kinetic modeling. To accelerate parameter estimation, we developed a C library for real-coded genetic algorithms (libRCGA). In libRCGA, two real-coded genetic algorithms (RCGAs), viz. the Unimodal Normal Distribution Crossover with Minimal Generation Gap (UNDX/MGG) and the Real-coded Ensemble Crossover star with Just Generation Gap (REX^star/JGG), are implemented in C language and paralleled by Message Passing Interface (MPI). We designed libRCGA to take advantage of high-performance computing environments and thus to significantly accelerate parameter estimation. Constrained optimization formulation is useful to construct a realistic kinetic model that satisfies several biological constraints. libRCGA employs stochastic ranking to efficiently solve constrained optimization problems. In the present paper, we demonstrate the performance of libRCGA through benchmark problems and in realistic parameter estimation problems. libRCGA is freely available for academic usage at http://kurata21.bio.kyutech.ac.jp/maeda/index.html.</p>

DOI： 10.2197/ipsjtbio.11.31

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130007483197

担当区分：責任著者   記述言語：英語   掲載種別：記事・総説・解説・論説等（学術雑誌）

© 2018 Bentham Science Publishers. Background: Cysteine S-sulfenylation is a major type of dynamic post-translational modification of the protein that plays an important role in regulating many biological processes in both of prokaryotic and eukaryotic species. To understand the function of S-sulfenylated proteins, identification of S-sulfenylation sites is an essential step. Due to numerous restrictions of experimental methods, computational prediction of the potential S-sulfenylation sites becomes popular. In this review, we discuss the recent development and challenges in protein S-sulfenylation site prediction from the available datasets, algorithms and accessible services. We also demonstrate the encountered limitation and future perspective of the computational prediction tools. Conclusion: The development of S-sulfenylation site prediction and their application is an emerging field of protein bioinformatics research. Accurate predictors are expected to identify general and species-specific S-sulfenylation sites when more experimental annotation data are available. Combining experimental and computational technologies will definitely accelerate an understanding of protein S-sulfenylation, discovering regulatory networks in living organisms.

DOI： 10.2174/0929866525666180905110619

Scopus

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担当区分：筆頭著者,　最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Background: Microbial production of biofuels and biochemicals from renewable feedstocks has received considerable recent attention from environmental protection and energy production perspectives. Many biofuels and biochemicals are produced by fermentation under oxygen-limited conditions following initiation of aerobic cultivation to enhance the cell growth rate. Thus, it is of significant interest to investigate the effect of dissolved oxygen concentration on redox regulation in Escherichia coli, a particularly popular cellular factory due to its high growth rate and well-characterized physiology. For this, the systems biology approach such as modeling is powerful for the analysis of the metabolism and for the design of microbial cellular factories. Results: Here, we developed a kinetic model that describes the dynamics of fermentation by taking into account transcription factors such as ArcA/B and Fnr, respiratory chain reactions and fermentative pathways, and catabolite regulation. The hallmark of the kinetic model is its ability to predict the dynamics of metabolism at different dissolved oxygen levels and facilitate the rational design of cultivation methods. The kinetic model was verified based on the experimental data for a wild-type E. coli strain. The model reasonably predicted the metabolic characteristics and molecular mechanisms of fnr and arcA gene-knockout mutants. Moreover, an aerobic-microaerobic dual-phase cultivation method for lactate production in a pfl-knockout mutant exhibited promising yield and productivity. Conclusions: It is quite important to understand metabolic regulation mechanisms from both scientific and engineering points of view. In particular, redox regulation in response to oxygen limitation is critically important in the practical production of biofuel and biochemical compounds. The developed model can thus be used as a platform for designing microbial factories to produce a variety of biofuels and biochemicals.

DOI： 10.1186/s13068-017-0867-0

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 Elsevier LtdBiological memory is a ubiquitous function that can generate a sustained response to a transient inductive stimulus. To better understand this function, we must consider the mechanisms by which different structures of genetic networks achieve memory. Here, we investigated two competitive gene regulatory network models: the regulated mutual activation network (MAN) and the regulated mutual repression network (MRN). Stochasticity deteriorated the persistence of memory of both the MAN and the MRN. Mathematical comparison by simulation and theoretical analysis identified functional differences in the stochastic memory between the competitive models: specifically, the MAN provided much more robust, persistent memory than the MRN. The stochastic persistent memory pattern of the MAN can be adjusted by changing the binding strength of the activators, whereas the MRN required highly cooperative and strong binding repressors for robust memory.

DOI： 10.1016/j.jtbi.2017.05.036

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 Masunaga et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The ErbB receptor signaling pathway plays an important role in the regulation of cellular proliferation, survival and differentiation, and dysregulation of the pathway is linked to various types of human cancer. Mathematical models have been developed as a practical complementary approach to deciphering the complexity of ErbB receptor signaling and elucidating how the pathways discriminate between ligands to induce different cell fates. In this study, we developed a simulator to accurately calculate the dynamic sensitivity of extracellular-signal-regulated kinase (ERK) activity (ERK∗) and Akt activity (Akt∗), downstream of the ErbB receptors stimulated with epidermal growth factor (EGF) and heregulin (HRG). To demonstrate the feasibility of this simulator, we estimated how the reactions critically responsible for ERK∗ and Akt∗ change with time and in response to different doses of EGF and HRG, and predicted that only a small number of reactions determine ERK∗ and Akt∗. ERK∗ increased steeply with increasing HRG dose until saturation, while showing a gently rising response to EGF. Akt∗ had a gradual wide-range response to HRG and a blunt response to EGF. Akt∗ was sensitive to perturbations of intracellular kinetics, while ERK∗ was more robust due to multiple, negative feedback loops. Overall, the simulator predicted reactions that were critically responsible for ERK∗ and Akt∗ in response to the dose of EGF and HRG, illustrated the response characteristics of ERK∗ and Akt∗, and estimated mechanisms for generating robustness in the ErbB signaling network.

DOI： 10.1371/journal.pone.0178250

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 The Royal Society of Chemistry. Cysteine S-sulfenylation is a major type of posttranslational modification that contributes to protein structure and function regulation in many cellular processes. Experimental identification of S-sulfenylation sites is challenging, due to the low abundance of proteins and the inefficient experimental methods. Computational identification of S-sulfenylation sites is an alternative strategy to annotate the S-sulfenylated proteome. In this study, a novel computational predictor SulCysSite was developed for accurate prediction of S-sulfenylation sites based on multiple sequence features, including amino acid index properties, binary amino acid codes, position specific scoring matrix, and compositions of profile-based amino acids. To learn the prediction model of SulCysSite, a random forest classifier was applied. The final SulCysSite achieved an AUC value of 0.819 in a 10-fold cross-validation test. It also exhibited higher performance than other existing computational predictors. In addition, the hidden and complex mechanisms were extracted from the predictive model of SulCysSite to investigate the understandable rules (i.e. feature combination) of S-sulfenylation sites. The SulCysSite is a useful computational resource for prediction of S-sulfenylation sites. The online interface and datasets are publicly available at http://kurata14.bio.kyutech.ac.jp/SulCysSite/.

DOI： 10.1039/c7mb00491e

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2016, Spandidos Publications. All rights reserved. Aurora kinase B (AURKB) inhibitors are regarded as potential molecular-targeting drugs for cancer therapy. The present study evaluated the cytotoxic effect of a combination of AZD1152-hQPA, an AURKB inhibitor, and various anticancer agents on the HeLa human cervical cancer cell line, as well as its cisplatin-resistant equivalent HCP4 cell line. It was demonstrated that AZD1152-hQPA had an antagonistic effect on the cytotoxicity of cisplatin, etoposide and doxorubicin, but had a synergistic effect on that of all-trans-retinoic acid (ATRA), Am80 and TAC-101, when tested on HeLa cells. Cisplatin, etoposide and doxorubicin were shown to increase the cellular expression of AURKB, while ATRA, Am80 and TAC-101 downregulated its expression. These results suggested that AURKB expression is regulated by these anticancer agents at the transcriptional level, and that the level of expression of AURKB may influence the cytotoxic effect of AZD1152-hQPA. Therefore, when using anticancer agents, decreasing the expression of AURKB using a molecular-targeting drug may be an optimal therapeutic strategy.

DOI： 10.3892/ol.2016.5156

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2015 The Society for Biotechnology, Japan. Chinese hamster ovary (CHO) cells are commonly used as the host cell lines concerning their ability to produce therapeutic proteins with complex post-translational modifications. In this study, we have investigated the time course extra- and intracellular metabolome data of the CHO-K1 cell line, under a control and stress conditions. The addition of NaCl and trehalose greatly suppressed cell growth, where the maximum viable cell density of NaCl and trehalose cultures were 2.2-fold and 2.8-fold less than that of a control culture. Contrariwise, the antibody production of both the NaCl and trehalose cultures was sustained for a longer time to surpass that of the control culture. The NaCl and trehalose cultures showed relatively similar dynamics of cell growth, antibody production, and substrate/product concentrations, while they indicated different dynamics from the control culture. The principal component analysis of extra- and intracellular metabolome dynamics indicated that their dynamic behaviors were consistent with biological functions. The qualitative pattern matching classification and hierarchical clustering analyses for the intracellular metabolome identified the metabolite clusters whose dynamic behaviors depend on NaCl and trehalose. The volcano plot revealed several reporter metabolites whose dynamics greatly change between in the NaCl and trehalose cultures. The elastic net identified some critical, intracellular metabolites that are distinct between the NaCl and trehalose. While a relatively small number of intracellular metabolites related to the cell growth, glucose, glutamine, lactate and ammonium ion concentrations, the mechanism of antibody production was suggested to be very complicated or not to be explained by elastic net regression analysis.

DOI： 10.1016/j.jbiosc.2015.12.013

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2016 The Author(s).Background: A kinetic model provides insights into the dynamic response of biological systems and predicts how their complex metabolic and gene regulatory networks generate particular functions. Of many biological systems, Escherichia coli metabolic pathways have been modeled extensively at the enzymatic and genetic levels, but existing models cannot accurately reproduce experimental behaviors in a batch culture, due to the inadequate estimation of a specific cell growth rate and a large number of unmeasured parameters. Results: In this study, we developed a detailed kinetic model for the central carbon metabolism of E. coli in a batch culture, which includes the glycolytic pathway, tricarboxylic acid cycle, pentose phosphate pathway, Entner-Doudoroff pathway, anaplerotic pathway, glyoxylate shunt, oxidative phosphorylation, phosphotransferase system (Pts), non-Pts and metabolic gene regulations by four protein transcription factors: cAMP receptor, catabolite repressor/activator, pyruvate dehydrogenase complex repressor and isocitrate lyase regulator. The kinetic parameters were estimated by a constrained optimization method on a supercomputer. The model estimated a specific growth rate based on reaction kinetics and accurately reproduced the dynamics of wild-type E. coli and multiple genetic mutants in a batch culture. Conclusions: This model overcame the intrinsic limitations of existing kinetic models in a batch culture, predicted the effects of multilayer regulations (allosteric effectors and gene expression) on central carbon metabolism and proposed rationally designed fast-growing cells based on understandings of molecular processes.

DOI： 10.1186/s12934-016-0511-x

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1007/s00449-016-1554-4

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.jbiosc.2015.12.001

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Singapore   Singapore   2015年11月23日  -  2015年11月26日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Malaysia   Kuala Lumpur   2015年11月15日  -  2015年11月19日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Malaysia   Kuala Lumpur   2015年11月15日  -  2015年11月19日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Iizuka   2015年03月05日  -  2015年03月06日

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Iizuka   2015年03月05日  -  2015年03月06日

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1186/1752-0509-8-S5-S1

Kyutacar

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Tokyo   2014年12月15日  -  2014年12月17日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.bej.2014.05.022

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

USA   San Antonio   2014年03月24日  -  2014年03月26日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1007/s00449-014-1167-8

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

細胞は,様々な環境の変化に絶えず直面しており,そのような摂動に対するシステムの感度を理解することは重要である.本研究では,感度解析や安定性解析によって,代謝反応システムの特性をロバストネスの観点から明らかにしようとした.その結果、システム全体のロバストネスを評価するマルチパラメータ感度は、シングルパラメータ感度の最大値と相関した。一方、代謝反応のネットワークサイズはシステム全体のロバストネスと相関がないことが示唆された.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110009675848

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Iizuka   2014年02月19日  -  2014年02月20日

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1252/jcej.13we152

Scopus

CiNii Article

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10031199937

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

アンモニアは大腸菌にとって最適な窒素源である.大腸菌は,TCA 回路の中間代謝物である α-ケトグルタル酸にアンモニアを付加し,グルタミン酸とグルタミンを合成する.細胞内の窒素のほとんどはこの 2 つの代謝物に由来するものである.このような理由から,大腸菌がどのようにアンモニアを同化し,グルタミン酸とグルタミンの合成を制御しているのか明らかにすることは重要である.我々は,大腸菌アンモニア同化システムの新しいダイナミックモデルを構築した.動力学パラメータ推定では,推定値と測定値の差が最小になるように遺伝的アルゴリズムにペナルティ戦略を組み合わせた.我々のモデルは,近年発表されたメタボロームデータを定量的に再現できる.最近,グルタミン酸合成酵素に対するアスパラギン酸の競争阻害の重要性が指摘されたが,本稿ではその検証も行う.また GOGAT 欠損株と GOGAT 欠損サプレッサー変異株の解析も行う.アンモニアが豊富な条件では,グルタミン酸の過剰な蓄積によってサプレッサー変異株は野生株よりも増殖が遅いことが予測された.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110009605329

記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.jbiosc.2013.03.010

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

A hierarchical clustering (HC) algorithm is one of the most widely used unsupervised statistical techniques for analyzing microarray gene expression data. When applying the HC algorithm to the gene expression data to cluster individuals, most of the HC algorithms generate clusters based on the highly differentially expressed (DE) genes that have very similar expression patterns. These highly DE genes may sometimes be irrelevant in biological processes. The serious problem is that those irrelevant genes with high expressions potentially drown out the low expressed genes that have important biological functions. To overcome the problem, Nowak and Tibshirani proposed the complementary hierarchical clustering (CHC) (Biostatistics, 9, 467-483, 2008). However, it is not robust against outlying expression and often produces misleading results if there exist some contaminations in the gene expression data. Thus, we propose the robust CHC (RCHC) method to robustify the CHC with respect to outliers by maximizing the β-likelihood function for sequential extraction of a gene-set with proper groups of individuals. Note that the proposed method reduces to the CHC with the tuning parameter β→0. A value of β plays a key role in the performance of the RCHC method, which controls the tradeoff between the robustness and efficiency of the estimators. Using simulation and real gene expression analysis, the RCHC method shows robust properties to gene expression clustering with respect to data contaminations, overcomes the problem of the CHC, and predicts critically important genes from breast cancer data.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110009657240

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1093/bib/bbt048

Scopus

記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.4236/abb.2013.43A063

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Iizuka   2013年02月28日  -  2013年03月01日

Kyutacar

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Bangladesh   Rajshahi   2012年12月22日  -  2012年12月24日

Kyutacar

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Bangladesh   Rajshahi   2012年12月22日  -  2012年12月24日

Kyutacar

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Tsuruoka   2012年10月21日  -  2012年10月25日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10031117614

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Korea   Deagu   2012年09月18日  -  2012年09月18日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1186/1751-0473-7-9

Kyutacar

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1007/s00449-012-0789-y

Scopus

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Australia   Adelaide   2012年07月09日  -  2012年07月12日

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Australia   Adelaide   2012年07月09日  -  2012年07月12日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1371/journal.pone.0037739

Kyutacar

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

次世代シークエンサーの登場によって,ヒトゲノムが驚くほど高速に解読できるようなった.さらに生体分子の網羅的測定技術が急速に進歩し,生物学的・医学的データがますます増大している.これらの膨大で複雑なデータを理解するために,バイオインフォマティクス,システムバイオロジーが誕生し,コンピュータシミュレーション技術を駆使して研究開発を行う時代を迎えている.このような世界的潮流を活性化するために,バイオメディカルインフォマティクス研究開発センターは,九州工業大学の強みである情報工学技術を先端的医学研究や医療関連技術開発に応用し,人類の健康と福祉に貢献する.本報告では,情報科学が代謝ネットワーク解析に有効である我々の研究例を紹介する.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110009569247

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1371/journal.pone.0030489

Kyutacar

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1162/artl_a_00049

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Malaysia   Kuala Lumpur   2011年11月30日  -  2011年12月02日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.bej.2011.02.022

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.jtbi.2010.12.012

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1007/s00449-010-0486-7

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

China   Shanghai   2011年05月11日  -  2011年05月15日

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

Kyutacar

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

Kyutacar

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

A goal of systems biology is to analyze large-scale molecular networks including gene expressions and protein-protein interactions, revealing the relationships between network structures and their biological functions. Dividing a protein-protein interaction (PPI) network into naturally grouped parts is an essential way to investigate the relationship between topology of networks and their functions. However, clear modular decomposition is often hard due to the heterogeneous or scale-free properties of PPI networks. To address this problem, we propose a diffusion model-based spectral clustering algorithm, which analytically solves the cluster structure of PPI networks as a problem of random walks in the diffusion process in them. To cope with the heterogeneity of the networks, the power factor is introduced to adjust the diffusion matrix by weighting the transition (adjacency) matrix according to a node degree matrix. This algorithm is named adjustable diffusion matrix-based spectral clustering (ADMSC). To demonstrate the feasibility of ADMSC, we apply it to decomposition of a yeast PPI network, identifying biologically significant clusters with approximately equal size. Compared with other established algorithms, ADMSC facilitates clear and fast decomposition of PPI networks. ADMSC is proposed by introducing the power factor that adjusts the diffusion matrix to the heterogeneity of the PPI networks. ADMSC effectively partitions PPI networks into biologically significant clusters with almost equal sizes, while being very fast, robust and appealing simple.

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79952277084&origin=inward

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10026689209

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Elementary mode (EM) analysis is potentially effective in integrating transcriptome or proteome data into metabolic network analyses and in exploring the mechanism of how phenotypic or metabolic flux distribution is changed with respect to environmental and genetic perturbations. The EM coefficients (EMCs) indicate the quantitative contribution of their associated EMs and can be estimated by maximizing Shannon's entropy as a general objective function in our previous study, but the use of EMCs is still restricted to a relatively small-scale networks. We propose a fast and universal method that optimizes hundreds of thousands of EMCs under the constraint of the Maximum entropy principle (MEP). Lagrange multipliers (LMs) are applied to maximize the Shannon's entropy-based objective function, analytically solving each EMC as the function of LMs. Consequently, the number of such search variables, the EMC number, is dramatically reduced to the reaction number. To demonstrate the feasibility of the MEP with Lagrange multipliers (MEPLM), it is coupled with enzyme control flux (ECF) to predict the flux distributions of Escherichia coli and Saccharomyces cerevisiae for different conditions (gene deletion, adaptive evolution, temperature, and dilution rate) and to provide a quantitative understanding of how metabolic or physiological states are changed in response to these genetic or environmental perturbations at the elementary mode level. It is shown that the ECF-based method is a feasible framework for the prediction of metabolic flux distribution by integrating enzyme activity data into EMs to genetic and environmental perturbations.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110007700578

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1016/j.jbiosc.2010.01.015

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110007619778

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1371/journal.pone.0012623

Kyutacar

Scopus

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Dynamic simulations are essential for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. However, typical dynamic modeling and analysis yield only local properties regarding a particular choice of plausible values of kinetic parameters, because it is hard to measure the exact values in vivo. Global and firm analyses are needed that consider how the changes in parameter values affect the results. A typical solution is to systematically analyze the dynamic behaviors in large parameter space by searching all plausible parameter values without any biases. However, a random search needs an enormous number of trials to obtain such parameter values. Ordinary evolutionary searches swiftly obtain plausible parameters but the searches are biased. To overcome these problems, we propose the two-phase search method that consists of a random search and an evolutionary search to effectively explore all possible solution vectors of kinetic parameters satisfying the target dynamics. We demonstrate that the proposed method enables a nonbiased and high-speed parameter search for dynamic models of biochemical networks through its applications to several benchmark functions and to the E. coli heat shock response model. © 2009 Information Processing Society of Japan.

DOI： 10.2197/ipsjtbio.2.2

Scopus

CiNii Article

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77951099999&origin=inward

担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

Bacterial cells evolve complex networks to survive nutrient starvation. The E. coli ammonia assimilation system consists of many positive and negative feedbacks for synthesizing glutamine and glutamate, the source of most nitrogen-containing compounds. Our objectives are to understand the molecular architecture of how those feedback loops act in concert for enhanced robustness with respect to ammonia depletion. The ammonia assimilation system is decomposed into the hierarchical modular structure in analogy to engineering control architecture. This modular architecture is elaborately designed to solve contradictory design issues. Comparison of biological modules with engineering systems identifies interesting biologically specific design features. © 2009 SICE.

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77951104212&origin=inward

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10026201207

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Kobe   2009年11月24日  -  2009年11月28日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Japan   Fukuoka   2009年08月18日  -  2009年08月21日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Motivation: Gene deletion and overexpression are critical technologies for designing or improving the metabolic flux distribution of microbes. Some algorithms including flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) predict a flux distribution from a stoichiometric matrix in the mutants in which some metabolic genes are deleted or non-functional, but there are few algorithms that predict how a broad range of genetic modifications, such as over- and underexpression of metabolic genes, alters the phenotypes of the mutants at the metabolic flux level. Results: To overcome such existing limitations, we develop a novel algorithm that predicts the flux distribution of the mutants with a broad range of genetic modification, based on elementary mode analysis. It is denoted as genetic modification of flux (GMF), which couples two algorithms that we have developed: modified control effective flux (mCEF) and enzyme control flux (ECF). mCEF is proposed based on CEF to estimate the gene expression patterns in genetically modified mutants in terms of specific biological functions. GMF is demonstrated to predict the flux distribution of not only gene deletion mutants, but also the mutants with underexpressed and overexpressed genes in Escherichia coli and Corynebacterium glutamicum. This achieves breakthrough in the a priori flux prediction of a broad range of genetically modified mutants. © The Author 2009. Published by Oxford University Press. All rights reserved.

DOI： 10.1093/bioinformatics/btp298

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=67649218402&origin=inward

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

Kyutacar

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

タンパク質相互作用 (PPI) ネットワークをモジュール分解するためにさまざまクラスタリング法が提案されているが、高速に正確なモジュールを発見する手法が確立されていない。本研究では、従来のスペクトル法に新規のベキ乗因子を加えることで、複雑なネットワークのわずかな幾何学的差を見いだし、クラスタに分解することができた。 PPI に存在する生体機能モジュールを位相幾何学的に見つけ出すための手法を開発した。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110007990807

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Kyutacar

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary, Escherichia coli, and Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110007042031

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Dynamic simulations are essential for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. However, typical dynamic modeling and analysis yield only local properties regarding a particular choice of plausible values of kinetic parameters, because it is hard to measure the exact values <i>in vivo</i>. Global and firm analyses are needed that consider how the changes in parameter values affect the results. A typical solution is to systematically analyze the dynamic behaviors in large parameter space by searching all plausible parameter values without any biases. However, a random search needs an enormous number of trials to obtain such parameter values. Ordinary evolutionary searches swiftly obtain plausible parameters but the searches are biased. To overcome these problems, we propose the two-phase search method that consists of a random search and an evolutionary search to effectively explore all possible solution vectors of kinetic parameters satisfying the target dynamics. We demonstrate that the proposed method enables a nonbiased and high-speed parameter search for dynamic models of biochemical networks through its applications to several benchmark functions and to the <i>E. coli</i> heat shock response model.

DOI： 10.11185/imt.4.377

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130000120679

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary, Escherichia coli, and Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants. © 2008 Elsevier Inc. All rights reserved.

DOI： 10.1016/j.jbiosc.2008.09.011

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=58149279036&origin=inward

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

China   Dailen   2008年10月12日  -  2008年10月17日

主要論文集（会議）

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

China   Dailen   2008年10月12日  -  2008年10月17日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10021982559

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

China   2008年10月12日  -  2008年10月17日

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

ダイナミックシミュレーションは環境ストレスや遺伝的変化に対してロバストネスを生み出す生化学ネットワークのメカニズムの解明に不可欠である。しかし、これまでに行われた多くのシミュレーションや解析は特定の速度パラメータ値に依存している。速度パラメータの正確な測定は困難であるので、特定のパラメータ値に依存するのではなく、パラメータ値の変化が与える影響を考慮した解析が必要である。これを可能にするためには細胞内の挙動を再現しうる全ての速度パラメータ値を広い探索空間から偏りなく探し出さなければならない。本稿では、ランダム探索と進化的探索を組み合わせた新しいパラメータ探索法、Two-phase search法を提案する。そして、この手法が偏りなく効率的に速度パラメータを探索できることを示す。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110006967151

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

For complex biological networks, graphical representations are highly desired for understanding some design principles, but few drawing methods are available that capture topological features of a large and highly heterogenous network, such as a protein interaction network. Here we propose the circular perspective drawing (CPD) method to visualize global structures of large complex networks. The presented CPD combines the quasi-continuous search (QCS) analogous to the steepest descent method with a random node swapping strategy for an enhanced calculation speed. The CPD depicts a network in an aesthetic manner by showing connection patterns between different parts of the network instead of detailed links between nodes. Global structural features of networks exhibited by CPD provide clues toward a comprehensive understanding of the network organizations. © 2008 Li, Kurata.

DOI： 10.1371/journal.pone.0002541

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=49749109867&origin=inward

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

Kyutacar

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（大学，研究機関等紀要）

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

中華民国   台北   2007年11月04日  -  2007年11月07日

主要論文集（会議）

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

中華民国   台北   2007年11月04日  -  2007年11月07日

主要論文集（会議）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Biochemical network maps are helpful for understanding the mechanism of how a collection of biochemical reactions generate particular functions within a cell. We developed a new and computationally feasible notation that enables drawing a wide resolution map from the domain-level reactions to phenomenological events and implemented it as the extended GUI network constructor of CADLIVE (Computer-Aided Design of LIVing systEms). The new notation presents 'Domain expansion' for proteins and RNAs, 'Virtual reaction and nodes' that are responsible for illustrating domain-based interaction and 'InnerLink' that links real complex nodes to virtual nodes to illustrate the exact components of the real complex. A modular box is also presented that packs related reactions as a module or a subnetwork, which gives CADLIVE a capability to draw biochemical maps in a hierarchical modular architecture. Furthermore, we developed a pathway search module for virtual knockout mutants as a built-in application of CADLIVE. This module analyzes gene function in the same way as molecular genetics, which simulates a change in mutant phenotypes or confirms the validity of the network map. The extended CADLIVE with the newly proposed notation is demonstrated to be feasible for computational simulation and analysis. © 2007 The Author(s).

DOI： 10.1093/nar/gkm769

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Dynamic simulations are necessary for understanding the mechanism of how biochemical network generate robust properties to environmental stresses or genetic changes. Sensitivity analysis allows the linking of robustness to network structure. However, it yields only local properties regarding a particular choice of plausible parameter values, because it is hard to know the exact parameter values in vivo. Global and firm results are needed that do not depend on particular parameter values. We propose mathematical analysis for robustness (MAR) that consists of the novel evolutionary search that explores all possible solution vectors of kinetic parameters satisfying the target dynamics and robustness analysis. New criteria, parameter spectrum width and the variability of solution vectors for parameters, are introduced to determine whether the search is exhaustive. In robustness analysis, in addition to single parameter sensitivity analysis, robustness to multiple parameter perturbation is defined. Combining the sensitivity analysis and the robustness analysis to multiple parameter perturbation enables identifying critical reactions. Use of MAR clearly identified the critical reactions responsible for determining the circadian cycle in the Drosophila interlocked circadian clock model. In highly robust models, while the parameter vectors are greatly varied, the critical reactions with a high sensitivity are uniquely determined. Interestingly, not only the per-timloop but also the dclk-cyc loop strongly affect the period of PER, although the dclk-cyc loop hardly changes its amplitude and it is not potentially influential. In conclusion, MAR is a powerful method to explore wide parameter space without human-biases and to link a robust property to network architectures without knowing the exact parameter values. MARS identifies the reactions critically responsible for determining the period and amplitude in the interlocked feedback model and suggests that the circadian clock intensively evolves or designs the kinetic parameters so that it creates a highly robust cycle. © 2007 Kurata et al.

DOI： 10.1371/journal.pone.0001103

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10019952371

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

現在、生命分子ネットワークの動的挙動を解明するために常微分方程式を用いた決定論的シミュレーションが盛んに行われている。しかし、細胞内の遺伝子発現は確率的に起こり、物質が拡散する。決定論的シミュレーションでは、パラメータが決定すると分子濃度の時間変化が決定する。そこで、確率的な遺伝子発現、時空間における物質の拡散を適用したシミュレーションを実現するために、新たな時空間モンテカルロシミュレーションの手法を提案する。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110006403660

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

ダイナミックシミュレーションはタンパク質や代謝物、遺伝子などから成る生命分子ネットワークの動的挙動を解析する手段である。生体内の動的挙動を再現するためには、リバースエンジニアリングの手法を用いて、多数の速度パラメータの値を決定する必要がある。我々はモジュール分割統合法と統計解析技術を組み合わせた最適化手法DIS(Decomposition and Integration with Statistical analysis)を開発した。これと遺伝的アルゴリズム(GA)を組み合わせることによって、通常のGAでは最適化困難な大規模生命分子ネットワークのパラメータ最適化に成功した。さらに、この最適化手法によってグローバルな最適解が得られた。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110006403659

担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

In the field of systems biology, biochemical networks are being reconstructed in computer to understand their dynamic features. In this study, we focused on the estimation problem for a dynamic model of the Drosophila circadian oscillator, which is defined by two evaluation functions that represent oscillatory features. However, since the search space is multimodal and logarithmically large, it is quite difficult for ordinary GAs to optimize this evaluation problem. Therefore, we had used two-step optimizing, a random search with GA. It successfully optimized the circadian oscillator, but required a long calculation time, causing a local search. On the other hand, to optimize two evaluation functions simultaneously, we proposed the survival ratio GA, where genes have lifetimes and a population holds search histories. By alternating two evaluation functions every generation, the population holds previously evaluated genes and children inherit each and mixed properties. The survival ratio GA exhibited wider space search and higher success ratio, thus we applied the one-step optimizing with the survival ratio GA to the circadian estimation problem, which shortens the total calculation times and finds out more local optimums than the previous two-step optimizing method. © 2006 IEEE.

DOI： 10.1109/ICSMC.2006.384687

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Background: In systems biology, network-based pathway analysis facilitates understanding or designing metabolic systems and enables prediction of metabolic flux distributions. Network-based flux analysis requires considering not only pathway architectures but also the proteome or transcriptome to predict flux distributions, because recombinant microbes significantly change the distribution of gene expressions. The current problem is how to integrate such heterogeneous data to build a network-based model. Results: To link enzyme activity data to flux distributions of metabolic networks, we have proposed Enzyme Control Flux (ECF), a novel model that integrates enzyme activity into elementary mode analysis (EMA). ECF presents the power-law formula describing how changes in enzyme activities between wild-type and a mutant are related to changes in the elementary mode coefficients (EMCs). To validate the feasibility of ECF, we integrated enzyme activity data into the EMCs of Escherichia coli and Bacillus subtilis wild-type. The ECF model effectively uses an enzyme activity profile to estimate the flux distribution of the mutants and the increase in the number of incorporated enzyme activities decreases the model error of ECF. Conclusion: The ECF model is a non-mechanistic and static model to link an enzyme activity profile to a metabolic flux distribution by introducing the power-law formula into EMA, suggesting that the change in an enzyme profile rather reflects the change in the flux distribution. The ECF model is highly applicable to the central metabolism in knockout mutants of E. coli and B. subtilis. © 2007 Kurata et al; licensee BioMed Central Ltd.

DOI： 10.1186/1752-0509-1-31

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：日本語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：日本語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

大腸菌GlnK ノックアウト株の窒素同化システムのダイナミックシミュレーションによって，環境中のアンモニア濃度の変化に対してシステムがヒステリシスを示すことが予測されている．このヒステリシス挙動がポジティブフィードバック制御に起因することを，シンプルモデルを用いた理論解析により明らかにした．シンプルモデルにおいて立式した3 次方程式を解くことによって，システムが複数の定常解を示すアンモニア濃度範囲が存在することが分かった．また，ポジティブフィードバック制御を強くすると，複数の定常解を示すアンモニアの濃度範囲が拡大し，逆に弱くすると，定常解が1 つになることを示した．Computer simulation predicted that the nitrogen assimilation system in the GlnK knockout mutant of E. coli shows hysteresis with respect to changes in the extracellular ammonia concentration. To theoretically elucidate the mechanism of how hysteresis is generated, we reduced the dynamic model to a simple model with third-order equations. Theoretical analysis of the simple model shows that a positive feedback control is responsible for hysteresis. The system has two steady-state solutions within a specific range of ammonia concentrations. The range that provides two solutions expands when the positive feedback becomes strong, while the system has only one solution when the positive feedback is weakened.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110006242974

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10020524742

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Advances in the postgenomic technology produce huge data regarding molecular interactions. Systems biology requires a model-based analysis to understand the molecular architecture of biological systems. Systems biology consists of four stages: network identification, system analysis, system control, and system design. First, a large-scale biochemical network model is reconstructed in computer by elucidating gene functions or by inferring gene regulation networks from postgenomic data. Second, we analyze the network architectures that generate robust properties to various types of perturbations and explore some design principles underlying molecular architectures. Third, dynamic behaviors are controlled at the molecular level. Finally, we develop new technologies to rationally design a biochemical system at the molecular levels.<br>

DOI： 10.2142/biophys.46.244

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110004810269

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/10018069281

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Biological systems have evolved complex regulatory mechanisms, even in situations where much simpler designs seem to be sufficient for generating nominal functionality. Using module-based analysis coupled with rigorous mathematical comparisons, we propose that in analogy to control engineering architectures, the complexity of cellular systems and the presence of hierarchical modular structures can be attributed to the necessity of achieving robustness. We employ the Escherichia coli heat shock response system, a strongly conserved cellular mechanism, as an example to explore the design principles of such modular architectures. In the heat shock response system, the sigma-factor σ32 is a central regulator that integrates multiple feedforward and feedback modules. Each of these modules provides a different type of robustness with its inherent tradeoffs in terms of transient response and efficiency. We demonstrate how the overall architecture of the system balances such tradeoffs. An extensive mathematical exploration nevertheless points to the existence of an array of alternative strategies for the existing heat shock response that could exhibit similar behavior. We therefore deduce that the evolutionary constraints facing the system might have steered its architecture toward one of many robustly functional solutions. © 2006 Kurata et al.

DOI： 10.1371/journal.pcbi.0020059

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

大腸菌の窒素同化システムにおいて、シミュレーションにより環境中のアンモニア濃度の変化に対してシステムがヒステリシスを示すことが予測されている。このヒステリシス挙動がポジティブフィードバック制御に起因することを、シンプルモデルを用いた理論解析により明らかにした。シンプルモデルにおいて立式した3次方程式を解くことによって、システムが複数の定常解を示すアンモニア濃度範囲があることがわかった。また、ポジティブフィードバック制御を強くすると、複数の定常解を示すアンモニアの濃度範囲が拡大し、逆に弱くすると、定常解が1つになることを示した。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110004849753

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

記述言語：日本語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

中華民国   Taipei   2006年04月  -  2006年04月

主要論文集（会議）

記述言語：日本語   掲載種別：研究論文（大学，研究機関等紀要）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

In the field of bioinformatics, several studies have attempted to reconstruct biological reactions on a computer in order to understand their essence. In this study, we optimized the parameter tuning problem of the heat shock response in E. coli, one of the gene regulatory network simulations, which exhibits a transient peak by genetic algorithms (GAs). However, if the search area is too large, the optimization performance deteriorated significantly. To optimize this problem more efficiently, we defined two evaluation functions that represent two features of the simulation and used the survival ratio GA. This GA has a gene's lifetime as a new concept, that is, the population holds previous search histories. By alternating between two evaluation functions every generation, the population holds both previously evaluated genes and children inherit both properties. In the two-evaluation problem of the heat shock response, the survival ratio GA exhibited a considerably better optimization performance than traditional GA methods. © 2005 IEEE.

Scopus

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担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

In the field of bioinformatics, biochemical networks have been reconstructed in computer to understand their dynamic features. A problem is how to estimate the values of many kinetic parameters that are hard to measure experimentally. In this study, we have proposed a novel parameter estimation method based on genetic algorithms (GAs) and applied it to the Drosophila circadian oscillator. We defined two evaluation functions that represent two features of the dynamic model. To optimize the two functions simultaneously, we proposed the survival ratio GA, which has a gene's lifetime as a new concept, that is, the population holds previous search histories. By alternating between two evaluation functions every generation, the population holds both previously evaluated genes and children inherit both properties. In the two-evaluation problem of the Drosophila circadian oscillation system, the survival ratio GA exhibited a considerably better optimizing performance than traditional GA methods. © 2005 IEEE.

Scopus

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Austria   2005年11月28日  -  2005年11月30日

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

米国   Hawaii   2005年10月10日  -  2005年10月12日

主要論文集（会議）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Motivation: Visualization is indispensable in the research of complex biochemical networks. Available graph layout algorithms are not adequate for satisfactorily drawing such networks. New methods are required to visualize automatically the topological architectures and facilitate the understanding of the functions of the networks. Results: We propose a novel layout algorithm to draw complex biochemical networks. A network is modeled as a system of interacting nodes on squared grids. A discrete cost function between each node pair is designed based on the topological relation and the geometric positions of the two nodes. The layouts are produced by minimizing the total cost. We design a fast algorithm to minimize the discrete cost function, by which candidate layouts can be produced efficiently. A simulated annealing procedure is used to choose better candidates. Our algorithm demonstrates its ability to exhibit cluster structures clearly in relatively compact layout areas without any prior knowledge. We developed Windows software to implement the algorithm for CADLIVE. © The Author 2005. Published by Oxford University Press. All rights reserved.

DOI： 10.1093/bioinformatics/bti290

Scopus

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記述言語：日本語   掲載種別：研究論文（学術雑誌）

主要雑誌

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Korea   Jezu Isaland   2005年04月  -  2005年04月

主要論文集（会議）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

We have developed the CADLIVE (Computer-Aided Design of LIVing systEms) Simulator that provided a rule-based automatic way to convert biochemical network maps into dynamic models, which enables simulating their dynamics without going through all of the reactions down to the details of exact kinetic parameters. The simulator supports the biochemical reaction maps that are generated by the previously developed GUI editor. Notice that the part of the GUI editor had been previously published, but, as yet, not the simulator. To directly link biochemical network maps to dynamic simulation, we have created the strategy of three layers and two stages with the efficient conversion rules in an XML representation. This strategy divides a molecular network into three layers, i.e., gene, protein, and metabolic layers, and partitions the conversion process into two stages. Once a biochemical map is provided, CADLIVE automatically builds a mathematical model, thereby facilitating one to simulate and analyze it. In order to demonstrate the feasibility of CADLIVE, we analyzed the Escherichia coli nitrogen-assimilation system (64 equations with 64 variables) that consists of multiple and complicated negative and positive feedback loops. CADLIVE predicted that the glnK gene is responsible for hysteresis or reversibility of nitrogen-related (Ntr) gene expression with respect to the ammonia concentration, supporting the experimental observation of the runaway expression of the Ntr genes. ©2005 by Cold Spring Harbor Laboratory Press.

DOI： 10.1101/gr.3463705

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Molecular biology studies the cause-and-effect relationships among microscopic processes initiated by individual molecules within a cell and observes their macroscopic phenotypic effects on cells and organisms. These studies provide a wealth of information about the underlying networks and pathways responsible for the basic functionality and robustness of biological systems. At the same time, these studies create exciting opportunities for the development of quantitative and predictive models that connect the mechanism to its phenotype then examine various modular structures and the range of their dynamical behavior. The use of such models enables a deeper understanding of the design principles underlying biological organization and makes their reverse engineering and manipulation both possible and tractable The heat shock response presents an interesting mechanism where such an endeavor is possible. Using a model of heat shock, we extract the design motifs in the system and justify their existence in terms of various performance objectives. We also offer a modular decomposition that parallels that of traditional engineering control architectures. © 2005 by The National Academy of Sciences of the USA.

DOI： 10.1073/pnas.0403510102

Scopus

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担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

The progress of computer made the analysis that was difficult in traditional technology possible. In Gene Regulatory Network Simulation to recreate and understand actual biological reaction, we build a reaction model and find the several unknown parameters in order to show the same behavior as actual. However it is difficult to optimize them because the scopes of them are logarithm scale wide and the fitness space is multidimensional and multimodal. We optimized it using Distributed Genetic Algorithms (DGA) which has multiple populations. DGA showed better performance, if and only if the parameter of the emigrating operation is appropriate. Therefore we propose Distributed and Integrated Genetic Algorithms (DIGA) to reduce the cost to find the appropriate parameters of operation. We carried out some optimizing experiments on parameter tuning of Heat Shock Response simulation of E.Coli and several mathematical functions and inspected the characteristic of DIGA. © 2004 IEEE.

Scopus

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記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

Kitakyushu   2004年10月17日  -  2004年10月21日

主要論文集（会議）

記述言語：英語   掲載種別：研究論文（学術雑誌）

Hague, Netherlands   2004年10月10日  -  2004年10月13日

主要論文集（会議）

記述言語：英語   掲載種別：研究論文（学術雑誌）

主要雑誌 代表的研究業績

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

A goal of systems biology is to build a concrete biochemical network map, which provides an important instruction to trace the pathways of interest or to understand the mechanism of a biological system. In the postgenomic era, not only the concrete biochemical maps, but also postgenomic maps (mRNA coexpression and protein-protein interaction networks) have been extensively produced. In the biochemical map, the individual reactions are reliable, but the number of the reactions is limited, because molecular biology requires extensive experiments to verify them. By contrast, postgenomic data provide much information regarding interactions, but are coarse-grained. To expand the biochemical network, an intuitional approach, which superposes postgenomic data on the map one by one, has been carried out, but it is not effective when a large amount of the coarse-grained data is handled. In order to effectively integrate such postgenomic interactions into a biochemical map, a statistical approach would be suitable rather than intuition. In this article, we proposed a novel statistical approach that integrates postgenomic interaction networks into the biochemical network, predicting novel pathways. A statistical correlation for such different types of networks identifies functional modules; subsequently the superposition of the different networks on the functional modules predicts inter-modular relations, which are the key pathways to construct a large-scale biochemical network.

DOI： 10.11234/gi1990.15.2_161

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003997360

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

A goal of systems biology is to build a concrete biochemical network map, which provides an important instruction to trace the pathways of interest or to understand the mechanism of a biological system. In the postgenomic era, not only the concrete biochemical maps, but also postgenomic maps (mRNA coexpression and protein-protein interaction networks) have been extensively produced. In the biochemical map, the individual reactions are reliable, but the number of the reactions is limited, because molecular biology requires extensive experiments to verify them. By contrast, postgenomic data provide much information regarding interactions, but are coarse-grained. To expand the biochemical network, an intuitional approach, which superposes postgenomic data on the map one by one, has been carried out, but it is not effective when a large amount of the coarse-grained data is handled. In order to effectively integrate such postgenomic interactions into a biochemical map, a statistical approach would be suitable rather than intuition. In this article, we proposed a novel statistical approach that integrates postgenomic interaction networks into the biochemical network, predicting novel pathways. A statistical correlation for such different types of networks identifies functional modules; subsequently the superposition of the different networks on the functional modules predicts inter-modular relations, which are the key pathways to construct a large-scale biochemical network.

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The further understanding of the mechanisms of the budding cell cycle networks requires the comprehensive map for the detailed signal transduction pathways and the integration of huge amounts of post-genomic data (DNA microarray and protein-protein interaction data) into such a map. The use of CADLIVE (<I>1</I>) constructed a detailed map of the budding yeast cell cycle, which consists of 184 molecules and 152 reactions, and integrated postgenomic data into the map by computationally exploring the signal transduction pathways. Consequently, the inconsistency between the detailed map and the post-genomic data greatly facilitated exploring novel or unexpected interactions among different processes. Biological predictions would be facilitated by exploring the interaction among the molecules that are located at distant processes on a map rather than by focusing on local signal transduction pathways intensively.

DOI： 10.11491/apcche.2004.0.419.0

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130005052462

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

現在,実数値遺伝的アルゴリズムは,多くの分野の最適化問題で利用されている.しかし,GAによる最適化では,トレードオフとして膨大な反復計算が要求される.そのため勾配を用いるハイブリッド遺伝的アルゴリズムが高い最適化性能を示している.しかし,評価値の勾配が計算できない最適化問題に対して勾配法GAの適用は困難である.そこで,このような問題を軽減する手法に優性方向優先探索法(Dominant Direction Priority Searching Method, DDP Searching Method)」がある.DDPでは母集団中の劣性個体から優性個体に向かうベクトルを間接的な評価値空間の勾配方向(優性方向)と仮定して,この方向を優先した局所探索と母集団の交叉を同時に行う.本論文では,数学的ベンチマーク関数と遺伝子発現ネットワークである大腸菌熱ショック応答シミュレーションの最適化問題DDP Searching Methodを用いて,その最適化性能の検証を行った.

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110002914187

担当区分：責任著者   掲載種別：研究論文（国際会議プロシーディングス）

GA is used in optimization problems in a lot of fields. But, there is a problem that GA demands a large quantity of computational complexity. Therefore we propose DDP algorithm in order to reduce this problem. DDP calculates DDP vector from the inferior gene to superior of population and create multiple new genes on the DDP vector. We carried out computer simulation to optimize some functions. As a result, DDP adds a search of a global area at early stage of optimization and a search of local area at a late stage to GA. GA+DDP showed the effectiveness in optimization problems of mathematical function and gene regulatory network simulation.

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

The further understanding of the mechanisms of gene regulatory networks requires comprehensive tools for both the representation of complicated signal transduction pathways and the in silico, identification of genomic signals that govern the regulation of gene expression. Consequently, sophisticated notation must be developed to represent the signal transduction pathways in a form that can be readily processed by both computers and humans. We propose the regulator-reaction equations combined with detailed attributes including the associated cellular component, molecular function, and biological process and present the simulation-directed graphical notation that is derived from modification of Kohn's method. We have developed the software suite, CADLIVE (Computer-Aided Design of LIVing systEms), which features a graphical user interface (GUI) to edit large-scale maps of complicated signal transduction pathways using a conventional XML-based representation. The regulator-reaction equations represent not only mechanistic reactions, but also semantic models containing ambiguous and incomplete processes. In order to demonstrate the feasibility of CADLIVE, we constructed a detailed map of the budding yeast cell cycle, which consists of 184 molecules and 152 reactions, in a really compact space. CADLIVE enables one to look at the whole view of a large-scale map, to integrate postgenomic data into the map, and to computationally simulate the signal transduction pathways, which greatly facilitates exploring novel or unexpected interactions.

DOI： 10.1093/nar/gkg461

Scopus

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記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌 代表的研究業績

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110002913118

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

現在、遺伝的アルゴリズムは、多くの分野の最適化問題で利用されている。しかし、トレードオフとして膨大な反復計算が要求される。そのため、冗長な計算負荷を軽減するためにDominant Direction Priority Searching Method(DDP Searching Method)」を提案する。DDPは従来のGA世代交代に追加されるアルゴリズムであり、勾配法の原理に基づき、母集団中の劣性個体から優性個体に向かう方向ベクトル(DD Vector)を評価値空間の勾配方向と仮定して新規探索点を設置する。このDDP Searching Methodを用いて、数学的ベンチマーク関数と大腸菌熱ショック応答シミュレーションでの最適化実験を行った結果、成功確率、計算回数ともに従来手法より良好な最適化性能を示した。

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/110002914201

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Las Vegas, Nevada, USA   2003年06月23日  -  2003年06月23日

記述言語：英語   掲載種別：研究論文（学術雑誌）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.14.611

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003812016

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.14.388

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003811903

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.14.609

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003812015

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

Anchorage   2002年05月15日  -  2002年05月15日

主要論文集（会議）

担当区分：責任著者   掲載種別：研究論文（学術雑誌）

To establish a strategy for stably and highly expressing a target gene in transformed plant cell suspensions, we developed the co-selection method that linked the hygromycin phosphotransferase gene (hph) to the β-glucuronidase (uidA, GUS) gene in the opposite direction under the same transcriptional regulation of the cauliflower mosaic virus (CaMV) 35S promoter. The linked genes were transferred into a tobacco BY-2 cell suspension, which was cultivated under various levels of the antibiotic pressure. Under the high pressure of hygromycin, GUS expression was increased and maintained over 1.5 years. We presented a successful example for selecting the plant cell suspension that highly expressed the target gene out of genetically heterogeneous cells. © 2002 Elsevier Science B.V. All rights reserved.

DOI： 10.1016/S1369-703X(01)00182-6

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.13.301

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003997192

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The bacterial heat shock response refers to the mechanism by which bacteria react to a sudden increase in the ambient temperature of growth. The consequences of such an unmediated temperature increase at the cellular level is the unfolding, misfolding, or aggregation of cell proteins, which threatens the life of the cell. Cells respond to the heat stress by initiating the production of heat-shock proteins whose function is to refold denatured proteins into their native states. The heat shock response, through the elevated synthesis of molecular chaperones and proteases, enables the repair of protein damage and the degradation of aggregated proteins. In a previous work [1], we have devised a dynamic model for the heat shock response in E. coli. In the present paper, we provide a thorough discussion of the dynamical nature of this model. We use sensitivity analysis and simulation tools to illustrate the remarkable efficiency, robustness, and stability of the heat shock response system.

DOI： 10.1109/ACC.2002.1023817

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.13.467

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003997275

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.11234/gi1990.12.284

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003997024

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The phenomenon known as RNA interference (RNAi) by double-stranded RNA (dsRNA) that was reported recently in the nematode Caenorhabditis elegans has been shown to operate by a mechanism that is widely conserved among species including plant cells. No quantitative analysis of the effects of RNAi on the expression of specific genes in plant cultured cells has been reported. An RNAi effect was observed 24 h after the introduction of dsRNA expression plasmids into tobacco BY-2 cells by electroporation. The simple system for suppression of specific genes in plant cells should be useful in attempts to elucidate the roles of individual genes in plant cells.

DOI： 10.1093/nass/1.1.235

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

A glucocorticoid-induced target gene expression system was used to control the expression of the uidA gene, whose product was β-glucuronidase (GUS), in tobacco BY-2 cell suspension culture. This targeting system showed quick, sensitive, and reversible response to dexamethazone (DEX), an artificial glucocorticoid hormone. Addition of DEX greatly and quickly enhanced uidA gene expression, whose level was as high as that under the control of the CaMV 35S promoter whereas in the absence of DEX, the GUS specific activity was suppressed to be as low as that of nontransformed BY-2 cells. The dilution of DEX decreased GUS specific activity showing that the concentration of DEX plays a major role in controlling the expression level of the target. The use of the glucocorticoid-induced system in plant cell suspension culture was demonstrated to precisely control target gene expression. (C) 2000 Elsevier Science S.A.

DOI： 10.1016/S1369-703X(00)00087-5

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Ribozymes are catalytic RNAs that can cleave RNAs at specific sites, thus they have been employed to degrade a target mRNA in vivo. Development of allosterically controllable ribozymes is of great current interest, but it remained difficult to furnish such functions to ribozymes in cultured cells or in animals. Recently, we designed allosterically controllable ribozymes termed maxizymes, which have sensor arms that recognize target mRNA sequences and, in the presence of such target sequences only, they form a cavity that can capture catalytically indispensable Mg2+ ions, cleaving the target The maxizyme was applied to therapy for chronic myelogenous leukemia (CML). It cleaved specifically the chimeric BCR-ABL mRNA, which caused CML, without damaging the normal ABL or BCR mRNA in mammalian cells and also in mice, providing the first successful example for allosteric control of the activity of artificial ribozymes in vivo.

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Anthocyanin production by strawberry cells depends not only on light intensity but also on the light/dark cycle operation with hour- or second- scale periods. These findings are useful for designing and operating photobioreactors for enhanced anthocyanin production. Intermittent illumination with a second-scale period produces the same amount of anthocyanin as continuous light, suggesting that the light intensity distribution within a photobioreactor does not cause suppressed production. In the hour-scale cycle, continuous light operation enhanced anthocyanin production more than the light/dark cycle process. (C) 2000 Elsevier Science Inc.

DOI： 10.1016/S0141-0229(00)00143-5

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0033994144&origin=inward

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

主要雑誌

記述言語：英語   掲載種別：研究論文（その他学術会議資料等）

記述言語：日本語   掲載種別：研究論文（その他学術会議資料等）

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

To accelerate the calculation speed for simulating a biological system, we proposed a novel simulation method, the two-phase partition method, which calculated molecular processes at a higher speed than any other proposed method. This method divides a biological system, which can be described by chemical reaction equations, into two-phases: the binding and reaction phases. We demonstrated the capability of the two-phase partition method to simulate a complex biological system at an extremely high speed and clarified the accuracy of the simulation. The two-phase partition method is very useful for simulating complex interactions among proteins and DNAs.

DOI： 10.11234/gi1990.11.185

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130003996847

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

To accelerate the calculation speed for simulating a biological system, we proposed a novel simulation method, the two-phase partition method, which calculated molecular processes at a higher speed than any other proposed method. This method divides a biological system, which can be described by chemical reaction equations, into two-phases: the binding and reaction phases. We demonstrated the capability of the two-phase partition method to simulate a complex biological system at an extremely high speed and clarified the accuracy of the simulation. The two-phase partition method is very useful for simulating complex interactions among proteins and DNAs.

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

The β-glucuronidase (GUS) reporter gene was fused to the 2.0-kb upstream region of Arabidopsis thaliana chalcone synthase (CHS) gene and transferred into BY-2 cells. CHS promoter expression showed a quick response to light/darkness and its expression level was more than that by the Cauliflower Mosaic Virus (CaMV) 35S promoter [1]. In this study, a kinetic model was developed for describing light-enhanced expression of the CHS promoter by tobacco BY-2 cells. This model simulates the behavior of CHS promoter expression by two factors: the specific light absorption rate (light intensity) and the illumination time. The dependency of GUS synthesis on light intensity is well characterized by using the Monod equation. The dependency on the illumination time is calculated by using a saturation time constant of illumination. The mathematical model demonstrated that the conditioned medium or past illumination changed the kinetics of CHS promoter expression.

DOI： 10.1016/S1369-703X(99)00034-0

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

To understand the elaborate system of a living organism, it is essential to know its "software", as well as its "hardware". The software of a living organism may be defined as the package of algorithms (methods and procedures) for its survival. The hardware of a living organism is encoded by genes on the chromosome. Its behaviors should be explainable on the basis of algorithms. The algorithms of a living system can be viewed as biological information that has been envolved over its long history of evolution. Among living organisms are bacteria that are probably the simplest systems for analyzing the software of living organisms. In the present paper, we describe our method for constructing a virtual bacterial system as a tool for analyzing the software of a living organism. We also describe bacterial algorithms for surviving during phosphate starvation and exhibiting an intelligent behavior called chemotaxis. In addition, we demonstrate a mobile robot whose behavior is controlled by a computer program designed on the basis of the bacterial chemotaxis algorithm.

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

We developed novel equipment that intermittently illuminates Coffea arabica cell suspensions at a second-scale interval and investigated how intermittent irradiation enhances caffeine biosynthesis by C. arabica cells. The light/dark cycles consisting of 2 s of illumination and 18 s of darkness enhanced caffeine production, reaching the same level as for continuous light. The intermittent illumination increased the production efficiency regarding light consumption by a factor of 10. Caffeine production was determined by light intensity regardless of intermittent or continuous light irradiation. We propose a new concept for designing a photobioreactor that is applicable to secondary metabolite production by plant cell culture.

DOI： 10.1021/bp980065u

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Enhanced expression of the rbcS3A promoter was achieved by overproducing phytochrome in BY-2 tobacco cells. The transformed cells contained the oat phytochrome A gene fused the 35S promoter of Cauliflower Mosaic Virus (CaMV) and the gus gene to the rbcS3A promoter. The transformed cells exhibited 1.5- to -2.8 fold enhanced the β-glucuronidase (GUS) activity when subjected to light.

DOI： 10.1023/A:1005484011673

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

The intermittent light irradiation with an hour-scale period is used for producing caffeine by Coffea arabica cells. Three factors concerning the light/dark cycle operation such as light intensity, the length of the cycle (period), and the ratio of the illumination time to the dark time (light/dark ratio) were investigated to optimize the caffeine production efficiency regarding light consumption. The light/dark ratio of 1/1 enhanced caffeine production, reaching the same level as continuous light; thus, the intermittent light irradiation improved the production efficiency twofold. The production was not influenced by the period, but was determined by light intensity regardless of intermittent or continuous light irradiation. Copyright (C) 1998 Elsevier Science Inc.

DOI： 10.1016/S0141-0229(98)00081-7

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The light-activated chalcone synthase (CHS) gene promoter was used to control the expression of a foreign gene - the uidA gene, whose product is β-glucuronidase (GUS) - in tobacco BY-2 cell suspensions. Light enhanced GUS specific activity rapidly and greatly in transgenic BY-2 containing a fusion of the CHS promoter and uidA gene. GUS production was turned on/off by using a light/dark cycle. The level of promoter activity was almost proportional to the intensity of light, surpassing the strength of the 35S promoter of Cauliflower Mosaic Virus (CaMV). Intermittent illumination induced the same level of GUS production as continuous light. The CHS promoter is thus useful for producing a foreign protein in plant cell bioreactors.

DOI： 10.1016/S0922-338X(98)80137-2

Scopus

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Light irradiation not only enhanced purine alkaloid (caffeine and theobromine) production by a Coffea arabica cell suspension culture, but also caused physiological changes in cell growth, and sugar and oxygen uptake rates. Both sugar and oxygen uptake rates showed maxima between 7 and 10 W/m 2 of light intensity, where the specific production rate reached the highest, although the specific cell growth rate was reduced by more than 50%. Light acts as a stress for enhanced production. The activities of enzymes related to purine alkaloid production were induced by light after a lag-time of 1 day. Light is an inducer for these enzymes. However, the de novo synthesis of purine alkaloids required at least 6 days of light irradiation. This discrepancy was caused by the insufficient supply of purine rings, the precursors for biosynthesis of purine alkaloids.

DOI： 10.1016/S0168-9452(96)04588-8

Scopus

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Since caffeine suppresses purine alkaloid (caffeine and theobromine) production by Coffea arabica cells, the effect of removing caffeine from the medium was investigated using the hydrophobic resin Amberlite XAD-4. An in situ removal method did not result in increased production because the adsorbent removed not only the products, but also essential components (hormones). Therefore, the use of an adsorption column employing the hydrophobic resin was investigated with a 35-d semicontinuous culture under light irradiation. Caffeine was removed within 30 min by the adsorption column on day 23 of the cultivation. In this system, the negative effects of hormone removal by the adsorbent were canceled out by the addition of fresh medium. This method increased alkaloid production 1.4-fold compared to the culture with no removal treatment. © 1994.

DOI： 10.1016/0922-338X(94)90192-9

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

Coffea arabica cells immobilized by calcium alginate gel were photocultured using a bubble‐column reactor under controlled light intensity. This process was carried out after their alkaloid productivity was improved by increasing the cell density in the initial gel matrix and preculturing the immobilized cells in the dark prior to light irradiation. The cells were grown in the form of a biofilm on gel beads, producing 100 mg/L of purine alkaloids in a 24‐day batch culture. Alkaloid production was relatively constant with respect to light intensity changes, and also cell growth was not suppressed much at high light intensity, with these behaviors being different from those obtained using suspended cells. These phenomena are explained by estimating the light intensity gradient within the cell‐immobilizing particles and by measuring the viable cell distribution within them. It subsequently suggests that the subsurface cells affect both the production and growth behaviors. © 1993 John Wiley & Sons, Inc. Copyright © 1993 John Wiley & Sons, Inc.

DOI： 10.1002/bit.260420413

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

A nonisotropic scattering model is proposed to estimate the light absorption rates in a heterogeneous photoreactor containing plant cells of Coffea arabica and is compared with an isotropic scattering model. In order to determine the directions of noniso‐tropically scattered light, optical theorems (geometrical optics and wave optics) are applied to light scattering caused by a homogeneous and perfect sphere. Two parameters, relative refractive index and attenuation coefficient, are used to characterize the ideal sphere. The primary feature of this model is that various phenomena of light scattering and absorption can be simulated by the combination of the two parameters. A measuring system composed of parallel plates was developed for evaluating the model. The nonisotropic scattering model was successfully applied to the heterogeneous reactor with the cultured plant cells. Copyright © 1993 American Institute of Chemical Engineers (AIChE)

DOI： 10.1021/bp00019a600

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担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The effect of light on caffeine production by Coffea arabica cells was investigated using chemical actinometry for the purpose of industrial application of plant cell cultures. Caffeine production by the Coffea arabica cells was greatly increased by light. About a six-day irradiation period was required to increase the caffeine production in a batch culture. Caffeine production significantly increased at a low light irradiation rate of 0.11 J/L/s. Meanwhile, cell growth was suppressed by increasing the irradiation rate. Maximum production was achieved at a moderate irradiation rate of 0.70 J/L/s in a 20-day batch culture. It was shown there was a light irradiation rate that optimized production. Since long-term continuous light greatly suppressed cell growth, the culture was divided into two stages: the production period in the light and the growth period in the dark. The high production and good growth were maintained for 65 days. © 1991, The Society of Chemical Engineers, Japan. All rights reserved.

DOI： 10.1252/jcej.24.783

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担当区分：責任著者   掲載種別：研究論文（学術雑誌）

DOI： 10.1111/j.1749-6632.1990.tb18216.x

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