Faculty Profiles - KURATA Hiroyuki

Papers - KURATA Hiroyuki

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PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides Reviewed International journal

Kurata H., Harun-Or-Roshid M., Tsukiyama S., Maeda K.

PLoS ONE 19 ( 8 ) 2024.08

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models Reviewed International journal

Kurata H., Harun-Or-Roshid M., Mehedi Hasan M., Tsukiyama S., Maeda K., Manavalan B.

Methods 227 37 - 47 2024.07

Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 20-O-methylation sites in human RNA Reviewed International journal

Harun-Or-Roshid M., Pham N.T., Manavalan B., Kurata H.

PLoS ONE 19 ( 6 June ) 2024.06

Stack-DHUpred: Advancing the accuracy of dihydrouridine modification sites detection via stacking approach Reviewed International journal

Harun-Or-Roshid M., Maeda K., Phan L.T., Manavalan B., Kurata H.

Computers in Biology and Medicine 169 2024.02

Elucidating Key Characteristics of PFAS Binding to Human Peroxisome Proliferator-Activated Receptor Alpha: An Explainable Machine Learning Approach Reviewed International journal

Maeda K., Hirano M., Hayashi T., Iida M., Kurata H., Ishibashi H.

Environmental Science and Technology 58 ( 1 ) 488 - 497 2024.01

CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction Reviewed International journal

Tsukiyama S., Hasan M.M., Kurata H.

Computational and Structural Biotechnology Journal 21 644 - 654 2023.01

MLAGO: machine learning-aided global optimization for Michaelis constant estimation of kinetic modeling Reviewed International journal

Maeda K., Hatae A., Sakai Y., Boogerd F.C., Kurata H.

BMC Bioinformatics 23 ( 1 ) 2022.12

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy Reviewed International journal

Hasan M.M., Tsukiyama S., Cho J.Y., Kurata H., Alam M.A., Liu X., Manavalan B., Deng H.W.

Molecular Therapy 30 ( 8 ) 2856 - 2867 2022.08

IACVP: Markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model Reviewed International journal

Kurata H., Tsukiyama S., Manavalan B.

Briefings in Bioinformatics 23 ( 4 ) 2022.07

BERT6mA: Prediction of DNA N6-methyladenine site using deep learning-based approaches Reviewed International journal

Tsukiyama S., Hasan M.M., Deng H.W., Kurata H.

Briefings in Bioinformatics 23 ( 2 ) 2022.03

TOPICS 医用工学・医療情報学世界初バーチャルヒト全身代謝モデルの開発と糖尿病への応用 Reviewed

倉田博之

医学のあゆみ 280 ( 9 ) 948 - 949 2022.02

Identification of a reliable sacral-sparing examination to assess the ASIA impairment scale in patients with traumatic spinal cord injury Reviewed International journal

Ariji Y., Hayashi T., Ideta R., Koga R., Murai S., Naka T., Ifuku R., Towatari F., Sakai H., Kurata H., Maeda T.

Journal of Spinal Cord Medicine 2022.01

Automatic Generation of SBML Kinetic Models from Natural Language Texts Using GPT Reviewed International journal

Maeda K., Kurata H.

International Journal of Molecular Sciences 24 ( 8 ) 2023.04

ICAN: Interpretable cross-attention network for identifying drug and target protein interactions Reviewed International journal

Kurata H., Tsukiyama S.

PLoS ONE 17 ( 10 October ) 2022.10

Recent Development of Bioinformatics Tools for microRNA Target Prediction Invited Reviewed International journal

Khatun M.S., Alam M.A., Shoombuatong W., Mollah M.N.H., Kurata H., Hasan M.M.

Current Medicinal Chemistry 29 ( 5 ) 865 - 880 2022.02

Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention–based neural networks Reviewed International journal

Tsukiyama S., Kurata H.

Computational and Structural Biotechnology Journal 20 5564 - 5573 2022.01

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning Reviewed

Hasan M.M., Alam M.A., Shoombuatong W., Deng H.W., Manavalan B., Kurata H.

Briefings in bioinformatics 22 ( 6 ) 2021.11

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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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LSTM-PHV: prediction of human-virus protein-protein interactions by LSTM with word2vec Reviewed International journal

Tsukiyama S., Hasan M.M., Fujii S., Kurata H.

Briefings in bioinformatics 22 ( 6 ) 2021.11

Critical evaluation of web-based DNA N6-methyladenine site prediction tools Invited Reviewed

Hasan M.M., Shoombuatong W., Kurata H., Manavalan B.

Briefings in Functional Genomics 20 ( 4 ) 258 - 272 2021.07

Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework Reviewed

Hasan M.M., Basith S., Khatun M.S., Lee G., Manavalan B., Kurata H.

Briefings in bioinformatics 22 ( 3 ) 2021.05

Prednts: Improved and robust prediction of nitrotyrosine sites by integrating multiple sequence features Reviewed

Nilamyani A.N., Auliah F.N., Moni M.A., Shoombuatong W., Hasan M.M., Kurata H.

International Journal of Molecular Sciences 22 ( 5 ) 1 - 11 2021.03

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations Reviewed

Hasan M.M., Alam M.A., Shoombuatong W., Kurata H.

Journal of Computer-Aided Molecular Design 35 ( 3 ) 315 - 323 2021.03

Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes Reviewed

Kurata H.

iScience 24 ( 2 ) 2021.02

Pup-fuse: Prediction of protein pupylation sites by integrating multiple sequence representations Reviewed

Auliah F.N., Nilamyani A.N., Shoombuatong W., Alam M.A., Hasan M.M., Kurata H.

International Journal of Molecular Sciences 22 ( 4 ) 1 - 12 2021.02

iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features Reviewed

Hasan M.M., Khatun M.S., Kurata H.

Genomics, Proteomics and Bioinformatics 2021.01

RCGAToolbox: A Real-coded Genetic Algorithm Software for Parameter Estimation of Kinetic Models Reviewed

Maeda K., Boogerd F.C., Kurata H.

IPSJ Transactions on Bioinformatics 14 30 - 35 2021.01

Language：English Publishing type：Research paper (scientific journal)

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

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Robust in-phase synchronization in repressor-based coupled gene oscillators Reviewed

Shamim Ul Hasan A.B.M., Dey S., Kurata H., Singh A.

IFAC-PapersOnLine 54 ( 15 ) 574 - 579 2021.01

RCGAToolbox: A Real-coded Genetic Algorithm Software for Parameter Estimation of Kinetic Models Reviewed

Maeda Kazuhiro, Boogerd Fred C., Kurata Hiroyuki

IPSJ Transactions on Bioinformatics 14 ( 0 ) 30 - 35 2021.01

Coupling protocol of interlocked feedback oscillators in circadian clocks Reviewed

Rashid M.M., Kurata H.

Journal of the Royal Society, Interface 17 ( 167 ) 2020.06

Computer-Aided Rational Design of Efficient NADPH Production System by Escherichia coli pgi Mutant Using a Mixture of Glucose and Xylose Reviewed

Matsuoka Y., Kurata H.

Frontiers in Bioengineering and Biotechnology 8 2020.04

Recent development of machine learning methods in microbial phos-phorylation sites Reviewed

Rashid M.M., Shatabda S., Hasan M.M., Kurata H.

Current Genomics 21 ( 3 ) 194 - 203 2020.01

i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes Reviewed

Hasan M.M., Manavalan B., Shoombuatong W., Khatun M.S., Kurata H.

Computational and Structural Biotechnology Journal 18 906 - 912 2020.01

A prediction model of functional outcome at 6 months using clinical findings of a person with traumatic spinal cord injury at 1 month after injury Reviewed

Ariji Y., Hayashi T., Ideta R., Koga R., Murai S., Towatari F., Terashi Y., Sakai H., Kurata H., Maeda T.

Spinal Cord 2020.01

ヒト全身代謝システムの数理モデル Invited Reviewed

倉田博之

細胞 52 376 - 379 2020.01

i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation Reviewed

Hasan M.M., Manavalan B., Shoombuatong W., Khatun M.S., Kurata H.

Plant Molecular Biology 2020.01

ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations Reviewed

Khatun M.S., Hasan M.M., Shoombuatong W., Kurata H.

Journal of Computer-Aided Molecular Design 2020.01

Evolution of sequence-based bioinformatics tools for protein-protein interaction prediction Reviewed

Khatun M.S., Shoombuatong W., Hasan M.M., Kurata H.

Current Genomics 21 ( 6 ) 454 - 463 2020.01

Authorship：Corresponding author Language：English Publishing type：Article, review, commentary, editorial, etc. (scientific journal)

© 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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Improvement of the memory function of a mutual repression network in a stochastic environment by negative autoregulation Reviewed International journal

Hasan A., Kurata H., Pechmann S.

BMC Bioinformatics 20 ( 1 ) 2019.12

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Computational identification of microbial phosphorylation sites by the enhanced characteristics of sequence information Reviewed International journal

Hasan M., Rashid M., Khatun M., Kurata H.

Scientific Reports 9 ( 1 ) 2019.12

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Ranking network mechanisms by how they fit diverse experiments and deciding on E. coli's ammonium transport and assimilation network Reviewed International journal

Maeda K., Westerhoff H., Kurata H., Boogerd F.

npj Systems Biology and Applications 5 ( 1 ) 2019.12

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Self-replenishment cycles generate a threshold response Reviewed International journal

Kurata H.

Scientific Reports 9 ( 1 ) 2019.12

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Efficient computational model for identification of antitubercular peptides by integrating amino acid patterns and properties Reviewed International journal

Khatun S., Hasan M., Kurata H.

FEBS Letters 593 ( 21 ) 3029 - 3039 2019.11

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Large-scale assessment of bioinformatics tools for lysine succinylation sites Invited Reviewed International journal

Hasan M.M., Khatun M.S., Kurata H.

Cells 8 ( 2 ) 2019.01

Prediction of: S -nitrosylation sites by integrating support vector machines and random forest Reviewed International journal

Hasan M., Manavalan B., Khatun M., Kurata H.

Molecular Omics 15 ( 6 ) 451 - 458 2019.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome Reviewed International journal

Hasan M., Manavalan B., Khatun M., Kurata H.

International Journal of Biological Macromolecules 2019.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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PreAIP: Computational prediction of anti-inflammatory peptides by integrating multiple complementary features Reviewed International journal

Khatun M., Hasan M., Kurata H.

Frontiers in Genetics 10 ( MAR ) 2019.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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SIPMA: A systematic identification of protein-protein interactions in Zea mays using autocorrelation features in a machine-learning framework Reviewed International journal

Khatun M., Hasan M., Mollah M., Kurata H.

Proceedings - 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering, BIBE 2018 122 - 125 2018.12

Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

© 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

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iLMS, computational identification of lysine-malonylation sites by combining multiple sequence features Reviewed International journal

Hasan M., Kurata H.

Proceedings - 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering, BIBE 2018 356 - 359 2018.12

Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

© 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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GPSuc: Global prediction of generic and species-specific succinylation sites by aggregating multiple sequence features Reviewed International journal

Hasan M., Kurata H.

PLoS ONE 13 ( 10 ) 2018.10

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Computational modeling of lysine post-translational modification: an overview. Invited Reviewed International journal

Curr Synthetic Sys Biol 6 1 2018.04

A novel isolation method for cancer prognostic factors via the p53 pathway by a combination of in vitro and in silico analyses Reviewed International journal

Oncoscience ( Impact Journals ) 5 88 - 98 2018.04

Long negative feedback loop enhances period tunability of biological oscillators Reviewed

Maeda K., Kurata H.

Journal of Theoretical Biology 440 21 - 31 2018.03

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Improved kinetic model of Escherichia coli central carbon metabolism in batch and continuous cultures Reviewed International journal

Kurata H., Sugimoto Y.

Journal of Bioscience and Bioengineering 125 ( 2 ) 251 - 257 2018.02

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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libRCGA: a C library for real-coded genetic algorithms for rapid parameter estimation of kinetic models Reviewed International journal

Maeda Kazuhiro, Boogerd Fred C., Kurata Hiroyuki

IPSJ Transactions on Bioinformatics 11 ( 0 ) 31 - 40 2018.01

A comprehensive review of in silico analysis for protein s-sulfenylation sites Invited Reviewed International journal

Hasan M., Khatun M., Kurata H.

Protein and Peptide Letters 25 ( 9 ) 815 - 821 2018.01

Authorship：Corresponding author Language：English Publishing type：Article, review, commentary, editorial, etc. (scientific journal)

© 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

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Modeling and simulation of the redox regulation of the metabolism in Escherichia coli at different oxygen concentrations Reviewed International journal

Matsuoka Y., Kurata H.

Biotechnology for Biofuels 10 ( 1 ) 183 2017.08

Mathematical comparison of memory functions between mutual activation and repression networks in a stochastic environment Reviewed International journal

Hasan A., Kurata H.

Journal of Theoretical Biology 427 28 - 40 2017.08

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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

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Robustness analysis of the detailed kinetic model of an ErbB signaling network by using dynamic sensitivity Reviewed International journal

Masunaga H., Sugimoto Y., Magi S., Itasaki R., Okada-Hatakeyama M., Kurata H.

PLoS ONE 12 ( 5 ) 2017.05

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Computational identification of protein S-sulfenylation sites by incorporating the multiple sequence features information Reviewed International journal

Hasan M., Guo D., Kurata H.

Molecular BioSystems 13 ( 12 ) 2545 - 2550 2017.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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

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In vitro evaluation of a combination treatment involving anticancer agents and an aurora kinase B inhibitor Reviewed International journal

Sakai S., Izumi H., Yoshiura Y., Nakayama Y., Yamaguchi T., Harada Y., Koi C., Kurata H., Morimoto Y.

Oncology Letters 12 ( 5 ) 4263 - 4269 2016.11

Language：English Publishing type：Research paper (scientific journal)

© 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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Metabolic analysis of antibody producing Chinese hamster ovary cell culture under different stresses conditions Reviewed

Badsha M., Kurata H., Onitsuka M., Oga T., Omasa T.

Journal of Bioscience and Bioengineering 122 ( 1 ) 117 - 124 2016.07

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli Reviewed International journal

Jahan N., Maeda K., Matsuoka Y., Sugimoto Y., Kurata H.

Microbial Cell Factories 15 ( 1 ) 2016.06

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

© 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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S-system-based Analysis of the Robust Properties Common to Many Biochemical Network Models Reviewed

Yu Matsuoka, Nusrat Jahan, Hiroyuki Kurata

Bioprocess and Biosystems Engineering 2016.03

Metabolic analysis of antibody producing CHO cell culture under different stresses conditions Reviewed

Md. Bahadur Badsha, Hiroyuki Kurata, Masayoshi Onitsuka, Takushi Oga, Takeshi Omasa

Journal of Bioscience and Bioengineering 2016.03

Web application for genetic modification flux with database to estimate metabolic fluxes of genetic mutants. Reviewed International journal

Noorlin Mohd Ali, Ryo Tsuboi, Yuta Matsumoto, Daisuke Koishi, Kazuhiro Maeda, Hiroyuki Kurata

Journal of Bioscience and Bioengineering 2016.03

Developing a kinetic model of the E. coli ammonium assimilation network International journal

Kazuhiro Maeda, Fred C. Boogerd, Hans V. Westerhoff, Hiroyuki Kurata

Proceedings of the 16th International Conference on Systems Biology 2015.11

A detailed kinetic model of E. coli central metabolism in a batch culture Reviewed International journal

Nusrat Jahan, Kazuhiro Maeda, Yu Matsuoka, Yurie Sugimoto, Hiroyuki Kurata,

Proceedings of Asian Congress on Biotechnology 2015 (ACB2015) 2015.11

Effect of NaCl and Trehalose Condition on Antibody Producing CHO Cell Culture Reviewed International journal

Md. Bahadur Badsha, Hiroyuki Kurata, Masayoshi Onitsuka, Takushi Oga, Takeshi Omasa

Proceedings of Asian Congress on Biotechnology 2015 (ACB2015) 2015.11

Synthesis and decomposition approach for rational design of a biochemical network International journal

Hiroyuki Kurata

Proceedings of the Third BMIRC International Symposium for Virtual Physiological Human 2015.03

Toward a quantitative in silico model for the E. coli ammonium assimilation system

Kazuhiro Maeda, Fred C. Boogerd, Frank J. Bruggeman, Hans V. Westerhoff, Hiroyuki Kurata

Proceedings of the Third BMIRC International Symposium for Virtual Physiological Human 2015.03

Analytical study of robustness of a negative feedback oscillator by multiparameter sensitivity Reviewed International journal

Kazuhiro Maeda, Hiroyuki Kurata

BMC Syst. Biol. 8 ( Suppl 5 ) S1 - S12 2014.12

Analytical study of robustness of a negative feedback oscillator by multiparameter sensitivity Reviewed

Kazuhiro Maeda, Hiroyuki Kurata

GIW/ISCB-Asia 2014 2014.12

Complementary elementary modes for fast and efficient analysis of metabolic networks Reviewed

Md. Bahadur Badsha, Hiroyuki Kurata

Biochem Eng J. 90 121 - 130 2014.06

Integration of omics into metabolic flux distribution by complementary elementary mode analysis for large-scale metabolic networks Reviewed

Md Bahadur Badsha, Hiroyuki Kurata

3rd International Conference and Exhibition on Metabolomics & Systems Biology 2014.03

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis, Reviewed

Bioproc. Biosys. Eng. 2014.03

S-systemを用いた代謝反応モデルの感度解析 Reviewed

松岡結 , NusratJahan , 倉田博之

IPSJ SIG technical reports ( Information Processing Society of Japan (IPSJ) ) 2014 ( 1 ) 1 - 2 2014.02

Aim and scope of the BMIRC at Kyutech

Hiroyuki Kurata

Proceedings of the Second BMIRC International Symposium on Advances in Bioinformatics and Medical Engineering 2014.02

Dynamic modeling of metabolic and gene regulatory systems toward developing virtual microbes Reviewed

Journal of Chemical Engineering of Japan 47 1 - 9 2014.01

バイオテクノロジー Reviewed

神谷典穂, 田中孝明, 宮坂武寛, 倉田博之, 近藤昭彦, 市川創作

化学工学 = Chemical engineering 77 ( 10 ) 719 - 724 2013.10

大腸菌アンモニア同化制御機構のダイナミックモデルの構築 Reviewed

前田和勲 , FredC.Boogerd , FrankJ.Bruggeman , HansV.Westerhoff , 倉田博之

IPSJ SIG technical reports ( Information Processing Society of Japan (IPSJ) ) 2013 ( 7 ) 1 - 6 2013.09

Robust Complementary Hierarchical Clustering for Gene Expression Data Analysis by β-Divergence Reviewed

J Biosci Bioeng. 116 397 - 407 2013.09

Robust complementary hierarchical clustering for gene expression data analysis by β-divergence Reviewed

Badsha Md. Bahadur, Mollah Md. Nurul Haque, Jahan Nusrat, Kurata Hiroyuki

Journal of bioscience and bioengineering 116 ( 3 ) 397 - 407 2013.09

BioFNet: Biological functional network database for analysis and synthesis of biological systems Reviewed

Hiroyuki Kurata, Kazuhiro Maeda, Toshikazu Onaka, Takenori Takata

Briefings in Bioinformatics 15 699 - 709 2013.07

Effect of cra gene mutation on the metabolism of Escherichia coli for a mixture of multiple carbon sources Reviewed

Ruilian Yao, Hiroyuki Kurata, Kazuyuki Shimizu

Advances in Bioscience and Biotechnology 4 477 - 486 2013.03

Bioalgorithms for rational design of biological systems

Hiroyuki Kurata

The Proceedings of the First BMIRC International Symposium on Frontiers in Computational Systems Biology and Bioengineering 2013.02

Metabolic Engineering for Systematic Organization and Analysis of Complex Metabolic Networks Reviewed

Md. Bahadur Badsha, Nusrat Jahan, Md. Nurul Haque Mollah, Hiroyuki Kurata

Proceedings of the International Conference on Statistical Data Mining for Bioinformatics Health Agriculture and Environment 2012.12

Sequential Extraction of Several Gene-sets with Proper Groups of Individuals for Gene Expression Data Analysis

Md. Bahadur Badsha, Nusrat Jahan, Md. Nurul Haque Mollah, Hiroyuki Kurata

Proceedings of the International Conference on Statistical Data Mining for Bioinformatics Health Agriculture and Environment 2012.12

Dynamic modeling of E. coli ammonia assimilation system Reviewed

Kazuhiro Maeda, Fred C. Boogerd, Hans V. Westerhoff, Frank J. Bruggeman, Hiroyuki Kurata

FOSBE 2012 2012.10

バイオテクノロジー Reviewed

神谷典穂, 田中孝明, 水本博, 倉田博之, 中崎清彦, 安部道玄, 酒井昇

化学工学 = Chemical engineering 76 ( 10 ) 608 - 613 2012.10

Computational framework for integration of metabolic flux analysis with its associated omics data Reviewed

Hiroyuki Kurata, Soma Tabata, Quanyu Zhao

Proceedings of the14th International Biotechnology Symposium and Exhibition (IBS2012) 2012.09

CADLIVE Optimizer: Web-based Parameter Estimation for Dynamic Models Reviewed

7 9 2012.08

Flux module decomposition for parameter estimation in a multiple-feedback loop model of biochemical networks Reviewed

Bioproc Biosys Eng 36 333 - 344 2012.07

Computational framework for integration of metabolic flux analysis with its associated omics data Reviewed

Hiroyuki Kurata, Soma Tabata, Quanyu Zhao

The 8th Asia-Pacific Conference on Algal Biotechnology (APCAB 2012) 55 2012.07

Application of Systems Biology for CO2 Fixation and Biofuel Production Using Microalgae Reviewed

Quanyu Zhao, Jiping Shi, Hiroyuki Kurata

The 8th Asia-Pacific Conference on Algal Biotechnology (APCAB 2012) 2012.07

Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps Reviewed

Kentaro Inoue, Shinichi Shimozono, Hideaki Yoshida, Hiroyuki Kurata

7 ( 6 ) e37739 2012.06

Biomedical Informatics R&D Center : Application of Informatics and Systems Engineering to Metabolic Systems Reviewed

KURATA Hiroyuki

IEICE technical report. Information theory ( The Institute of Electronics, Information and Communication Engineers ) 112 ( 58 ) 19 - 21 2012.05

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

Next generation sequencers enable decoding human genome at a surprisingly high speed. Furthermore, biological and medical data have rapidly been produced due to the development of systemic high-throughput technologies. Bioinformatics and systems biology have emerged, facilitating the interdisciplinary research and development among medicine, informatics, and engineering. In such a world-wide stream, we extensively apply the information technology and systems engineering to the research and development of medicine and medical care systems. In this study, we demonstrate that information technology is effective in analysis of metabolic networks.

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/110009569247

A Symmetric Dual Feedback System Provides a Robust and Entrainable Oscillator Reviewed

Kazuhiro Maeda, Hiroyuki Kurata

PLoS ONE 7 ( 2 ) e30489 2012.02

Biological design principles of complex feedback modules in the E. coli ammonia assimilation system Reviewed

Koichi Masaki, Kazuhiro Maeda, Hiroyuki Kurata

Artificial Life 18 53 - 90 2012.01

Grid layout algorithm for biochemical networks using approximate pattern matching Reviewed

Kentaro Inoue, Sinichi Shimozono, Hiroyuki Kurata

International Conference on Bioinformatics (InCoB2011) 229 2011.11

Quasi-multiparameter sensitivity measure for robustness analysis of complex biochemical networks Reviewed

Kazuhiro Maeda, Hiroyuki Kurata

J Theor Biol 272 174 - 186 2011.08

CADLIVE Converter for constructing a biochemical network map Reviewed

Kentaro Inoue, Sayaka Tomeda, Shinpei Tonami, Yuki Shimokawa, Masayo Ono, Hiroyuki Kurata

Biochem Eng J 54 200 - 206 2011.08

An integrative and practical evolutionary optimization for a complex, dynamic model of biological networks Reviewed

Kazuhiro Maeda, Yuya Fukano, Shunsuke Yamamichi, Daichi Nitta, Hiroyuki Kurata

Bioproc Biosys Eng 34 433 - 446 2011.08

Maximum entropy principle optimizes the large-scale elementary modes for a broad range of genetic mutants Reviewed

Hiroyuki Kurata, Quanyu Zhao

Proceedings of Asian Congress on Biotechnology B0768 2011.05

生体分子ネットワークレイアウトのための2次元近似照合によるハイブリッドレイアウトアルゴリズム

井上健太郎、下園真一、吉田英聡、倉田博之

情報処理学会研究報告 BIO-２４ ( 6 ) 1 - 6 2011.03

概日リズムのフィードバックシステムのロバストネス解析

前田和勲、倉田博之

情報処理学会研究報告 BIO-２４ ( 7 ) 1 - 6 2011.03

Diffusion model based spectral clustering for protein-protein interaction networks. Reviewed

Inoue K., Li W., Kurata H.

PloS one 5 ( 9 ) 2010.12

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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.

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バイオテクノロジー Reviewed

池田宰, 上田宏, 大河内美奈, 吉見靖男, 倉田博之, 木村幸敬

化学工学 = Chemical engineering 74 ( 10 ) 570 - 576 2010.10

Use of maximum entropy principle with Lagrange multipliers extends the feasibility of elementary mode analysis Reviewed

Zhao Quanyu, Kurata Hiroyuki

Journal of bioscience and bioengineering 110 ( 2 ) 254 - 261 2010.08

Use of maximum entropy principle with Lagrange multipliers extends the feasibility of elementary mode analysis Reviewed

J Biosci Bioeng 110 254 - 261 2010.08

JABEE認定校のカリキュラムと教育内容の特色 : (3) 九州工業大学生命情報工学科のプログラム Reviewed

倉田博之, 清水和幸

生物工学会誌 : seibutsu-kogaku kaishi 88 ( 5 ) 233 - 236 2010.05

Diffusion Model Based Spectral Clustering For Protein-Protein Interaction Networks Reviewed

Kentaro Inoue, Weijiang Li and Hiroyuki Kurata

PLOS ONE 5 e12623 2010.04

Two-phase search (TPS) method: Nonbiased and high-speed parameter search for dynamic models of biochemical networks Reviewed

Maeda K., Kurata H.

IPSJ Transactions on Bioinformatics 2 2 - 14 2009.12

Module-based analysis of the robustness generated by complex feedback regulations in biological networks Reviewed

Kurata H.

ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings 192 - 195 2009.12

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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.

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バイオテクノロジー Reviewed

倉田博之, 中野秀雄, 大河内美奈, 吉見靖男, 池田宰, 吉井英文

化学工学 = Chemical engineering 73 ( 10 ) 506 - 512 2009.10

Module-based analysis of the robustness generated by complex feedback regulations in biological networks Reviewed

Hiroyuki Kurata

Proceedings of ICROS-SICE International Joint Conference 2009 1A11-101 2009.08

Elementary model-based prediction of the flux distribution for a variety of genetic mutants Reviewed

Quanyu Zhao, Hiroyuki Kurata

J Biosci Bioeng: Proceedings of APBioCHEC'2009 108 S165 2009.08

Genetic modification of flux for flux prediction of mutants Reviewed

Bioinformatics 25 1702 - 1708 2009.07

Genetic modification of flux for flux prediction of mutants Reviewed

Zhao Q., Kurata H.

Bioinformatics 25 ( 13 ) 1702 - 1708 2009.06

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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スペクトル法によるタンパク質相互作用ネットワークのモジュール分解,

井上健太郎 Weijiang Li, 倉田博之

情報処理学会研究報告 BIO-17 ( 14 ) 1 - 4 2009.05

概日リズムのインターロックフィードバックのロバストネス解析

前田和勲倉田博之

情報処理学会研究報告 BIO-17 ( 15 ) 1 - 5 2009.05

Modular decomposition based spectrum for protein-protein interaction network Reviewed

INOUE Kentaro, LI Weijiang, KURATA Hiroyuki

情報処理学会研究報告. BIO, バイオ情報学 = IPSJ SIG technical reports 17 H1 - H4 2009.05

Two-phase search (TPS) method: Nonbiased and high-speed parameter search for dynamic models of biochemical networks Reviewed

IPSJ Transaction on Bioinformatics ２ 2 - 14 2009.04

Maximum entropy decomposition of flux distribution at steady state to elementary modes Reviewed

J Biosci Bioeng 107 84 - 89 2009.03

A gradual update method for simulating the steady-state solution of stiff differential equations in metabolic circuits Reviewed

32 283 - 288 2009.02

Maximum entropy decomposition of flux distribution at steady state to elementary modes Reviewed

Zhao Quanyu, Kurata Hiroyuki

Journal of bioscience and bioengineering 107 ( 1 ) 84 - 89 2009.01

Two-phase Search (TPS) Method: Nonbiased and High-speed Parameter Search for Dynamic Models of Biochemical Networks Reviewed

Maeda Kazuhiro, Kurata Hiroyuki

Information and Media Technologies 4 ( 2 ) 377 - 389 2009.01

Maximum entropy decomposition of flux distribution at steady state to elementary modes Reviewed

Zhao Q., Kurata H.

Journal of Bioscience and Bioengineering 107 ( 1 ) 84 - 89 2009.01

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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CADLIVE: Computer aided design of biochemical systems Reviewed

Supplement of Journal of Biotechnology:13 th International Biotechnology Symposium and Exhibition (IBS2008) I4-O-001 2008.10

Computer-aided rational design of the phosphotransferase system for enhanced glucose uptake in Escherichia coli. Reviewed

Yousuke Nishio, Yoshihiro Usuda, Kazuhiko Matsui, Hiroyuki Kurata

Supplement of Journal of Biotechnology:13 th International Biotechnology Symposium and Exhibition (IBS2008) I1-O-071 2008.10

バイオテクノロジー Reviewed

酒井康行, 中野秀雄, 吉本誠, 倉田博之, 池田宰, 橋本篤

化学工学 = CHEMICAL ENGINEERING OF JAPAN 72 ( 10 ) 551 - 557 2008.10

Prediction of flux distribution of mutants by enzyme control fluxes with maximum entropy principal Reviewed

Quanyu Zhao, Hiroyuki Kurata

Supplement of Journal of Biotechnology: 13 th International Biotechnology Symposium and Exhibition (IBS2008) 2008.10

Two-phase search (TPS) 法 : 動的生化学ネットワークモデルの偏りのない効率的なパラメータ探索 Reviewed

前田和勲, 倉田博之

情報処理学会研究報告. BIO, バイオ情報学 = IPSJ SIG technical reports 14 9 - 12 2008.09

動的生化学ネットワークモデルの偏りのない効率的なパラメータ探索

前田和勲，倉田博之

情報処理学会研究報告 BIO-14 9 - 12 2008.08

Visualizing global properties of large complex networks Reviewed

Li W., Kurata H.

PLoS ONE 3 ( 7 ) 2008.07

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Estimation of Intracellular Flux Distribution under Underdetermined and Uncertain Conditions by Maximum Entropy Principle Reviewed

Quanyu Zhao,Hiroyuki Kurata

Chin J Biotech Chin 24: 24 21352136 - 21352136 2008.04

Maximum entropy decomposition of flux distribution at steadystate to elementary modes Reviewed

Quanyu Zhao,Hiroyuki Kurata

J Biosci Bioeng 107 8489 - 8489 2008.04

A gradual update method for simulating the steady-state solution of stiff differential equations in metabolic circuits Reviewed

Emi Shiraishi Kazuhiro Maeda Hiroyuki Kurata

Bioprocess Biosyst. Eng 32 283288 - 283288 2008.04

Visualizing Global Properties of Large Complex Networks Reviewed

Li W.,Kurata H.

PLoS ONE 3 e2541 - e2541 2008.04

Computer-aided rational design of the phosphotransferase system for enhanced glucose uptake in Escherichia coli Reviewed

Yousuke Nishio,Yoshihiro Usuda,Kazuhiko Matsui,Hiroyuki Kurata

Molecular Systems Biology 4 160 - 160 2008.04

Two-phase search (TPS) method: Nonbiased and efficient parameter search for dynamic models of biochemical networks.

Maeda,K.,Kurata,H.

IPSJ SIG Technical Report BIO-14 9 - 12 2008.04

CADLIVE for Construction and Dynamic Simulation of Biochemical Networks Reviewed

Kazuhiro Maeda,Hiroyuki Kurata

Proceedings of Asia Pacific Biochemical Engineering Conference ( J0013 ) 2007.11

Systems Biology of the Nitrogen Assimilation System in E.coli Reviewed

Koichi Masaki,Hiroyuki Kurata

Proceedings of Asia Pacific Biochemical Engineering Conference J0108 - J0108 2007.11

Extended CADLIVE: A novel graphical notation for design of biochemical network maps and computational pathway analysis Reviewed

Kurata H., Inoue K., Maeda K., Masaki K., Shimokawa Y., Zhao Q.

Nucleic Acids Research 35 ( 20 ) 2007.11

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Mathematical identification of critical reactions in the interlocked feedback model Reviewed

Kurata H., Tanaka T., Ohnishi F.

PLoS ONE 2 ( 10 ) 2007.10

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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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生物情報 Reviewed

倉田博之

化学工学 = CHEMICAL ENGINEERING OF JAPAN 71 ( 10 ) 682 - 683 2007.10

A Stochastic Simulation of Diffusion Reaction Model in Embryo Development Reviewed

NAKANO Katsutoshi, IWASAKI Rei, KURATA Hiroyuki

IPSJ SIG Notes ( Information Processing Society of Japan (IPSJ) ) 66 95 - 98 2007.09

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

The deterministic simulation that uses ordinary differential equations to clarify dynamic behaviors of life-giving molecular networks is actively implemented now. However, gene expressions in cells happen stochastically and materials diffusion. In the deterministic simulation, time variations of molecular concentrations are decided when parameters are decided. Therefore, we propose the new method of spatiotemporal Monte Carlo simulation for achieving the simulation applied to gene expression and diffusion of materials in space and time.

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/110006403660

Global Optimization of Large-scale Dynamic Biomolecular Network Model Reviewed

MAEDA KAZUHIRO, YOSHIDA KEISUKE, KURATA HIROYUKI

IPSJ SIG Notes ( Information Processing Society of Japan (IPSJ) ) 66 91 - 94 2007.09

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

Dynamic simulation is a way to analyze dynamics of biomolecular networks consisting of proteins, metabolites and genes. In order to simulate their intrinsic dynamics, it is necessary to optimize the values of many kinetic parameters by reverse-engineering. We developed a new optimization method, DIS (Decomposition and Integration with Statistical analysis) combining decomposition and integration method with statistical analysis. By using DIS and genetic algorithm (GA), we optimized the parameters of large-scale biomolecular network which conventional GA cannot optimize. In this article, we also show that this method can obtain global solutions.

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/110006403659

Effective and fast optimization for a dynamic model of the Drosophila circadian oscillator Reviewed

Tanaka S., Kurata H., Ohashi T.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 5 3596 - 3601 2007.08

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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

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Integration of enzyme activities into metabolic flux distributions by elementary mode analysis Reviewed

Kurata H., Zhao Q., Okuda R., Shimizu K.

BMC Systems Biology 1 2007.07

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Integration of enzyme activities into metabolic flux distributions by elementary mode analysis Reviewed

Hiroyuki Kurata,Quanyu Zhao,Ryuichi Okuda,Kazuyuki Shimizu

BMC Systems Biology 1 31 - 31 2007.04

Mathematical identification of critical reactions in the interlocked feedback model Reviewed

H. Kurata,T. Tanaka,F. Ohnishi

PLoS One 2 e1103 - e1103 2007.04

Extended CADLIVE: a novel graphical notation for designing a biochemical network map that enables computational pathway analysis Reviewed

Hiroyuki Kurata,Kentaro Inoue,Kazuhiro Maeda,Koichi Masaki,Yuki Shimokawa,Quanyu Zhao

Nucleic Acids Res 35 e134 - e134 2007.04

大腸菌窒素同化システムのポジティブフィードバック制御のシンプルモデル Reviewed

真崎浩一，倉田博之

情報処理学会論文誌数理モデル化と応用 48 104 - 109 2007.04

大規模な動的生命分子ネットワークモデルのグローバルな最適化

前田和勲，吉田圭介，倉田博之

情報処理学会研究報告 MPS-66 91 - 94 2007.04

胚発生における拡散反応モデルの確率的シミュレーション

中野克俊，岩崎麗，倉田博之

情報処理学会研究報告 MPS-66 95 - 98 2007.04

A Simple Model of Positive Feedback of the Nitrogen Assimilation System in E. coli Reviewed

MASAKI KOICHI, KURATA HIROYUKI

情報処理学会論文誌数理モデル化と応用(TOM) ( Information Processing Society of Japan (IPSJ) ) 48 ( 6 ) 104 - 109 2007.03

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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

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Bioinformatics Reviewed

倉田博之

化学工学 = CHEMICAL ENGINEERING OF JAPAN 70 ( 10 ) 2006.10

Systems Biology and Design of Biological Systems Reviewed

KURATA Hiroyuki

Seibutsu Butsuri ( The Biophysical Society of Japan General Incorporated Association ) 46 ( 5 ) 244 - 250 2006.09

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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.

DOI： 10.2142/biophys.46.244

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/110004810269

CADLIVE : Computer-Aided Design of biological systems and its application Reviewed

KURATA Hiroyuki

Bioscience & industry 64 ( 9 ) 508 - 511 2006.09

Module-based analysis of robustness tradeoffs in the heat shock response system Reviewed

Kurata H., El-Samad H., Iwasaki R., Ohtake H., Doyle J., Grigorova I., Gross C., Khammash M.

PLoS Computational Biology 2 ( 7 ) 0663 - 0675 2006.08

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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A Simple model of positive feedback of the nitrogen assimilation system in E. coli Reviewed

MASAKI Koichi, KURATA Hiroyuki

IPSJ SIG Notes ( Information Processing Society of Japan (IPSJ) ) 59 61 - 64 2006.05

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

Computer simulation predicted that the nitrogen assimilation system shows hysteresis with respect to the change in ammonia concentration in environment. To theoretically elucidate the mechanism of how hysteresis is generated, we reduced the dynamic model to the simple model with the third-order equations. Theoretical analysis of the simple model shows that the positive feedback control is responsible for hysteresis. The system has two steady-state solutions for the ammonia concentration within specific ranges. The range of an ammonia concentration 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

Other Link： https://ci.nii.ac.jp/naid/110004849753

Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System Reviewed

H. Kurata,H. El Samad,R. Iwasaki,H. Othake,J.C. Doyle,I. Grigorova,C. Gross,and M. Khammash

PLoS Computational Biology 2 e59 - e73 2006.05

システムバイオロジーの現状と未来 Reviewed

倉田　博之

生物物理 46 244 - 250 2006.04

Effective and fast optimization for a dynamic model of the Drosophila circadian oscillator Reviewed

Shin Tanaka,Hiroyuki Kurata,Takeshi Ohashi

IEEE International Conference on Systems, Man, and Cybernetics 3596 - 3601 2006.04

CADLIVE: Integration for large-scale network data

Yuki Shimokawa,Zazuhiro Maeda,Kentaro Inoue,Hiroyuki Kurata

The 16th International Conference on Genome Informatics S02-1-2 2006.04

A steady-state approximation-based solver for stiff biochemical models

Emi Shiraishi,Hiroyuki Kurata

The 16th International Conference on Genome Informatics P016-1-2 2006.04

Comparison of the prediction abilities of FBA, MOMA, and ROOM for a pykF mutant of E. coli

Quanyu Zhao,Hiroyuki Kurata

The 16th International Conference on Genome Informatics P107-1-2 2006.04

Sensitivity analysis for the E. coli nitrogen assimilation system

Koichi Masaki,Hiroyuki Kurata

P010-1-2 2006.04

A simple model of positive feedback of the nitrogen assimilation system in E. coli

Masaki Kouichi,Kurata Hiroyuki

ISPJ SIG Technical Reports 61 - 64 2006.04

Survival ratio GA for two-evaluation problem in parameter tuning of heat shock response in E. coli Reviewed

Tanaka S., Kurata H., Ohashi T.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 3 2078 - 2083 2005.12

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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.

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Reverse engineering for a dynamic model of the Drosophila circadian oscillator Reviewed

Tanaka S., Kurata H., Ohashi T.

Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet 1 625 - 632 2005.12

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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.

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Reverse Engineering for a Dynamic Model of the Drosophila Circadian Oscillator Reviewed

Shin Tanaka,Hiroyuki Kurata,Takeshi Ohashi

International Conference on Computational Intelligence for Modelling, Control and Automation 625 - 631 2005.11

Survival ratio GA for two-evaluation problem in parameter tuning of heat shock response in E. coli Reviewed

Shin Tanaka,Hiroyuki Kurata,Takeshi Ohashi

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics 2078 - 2083 2005.10

A grid layout algorithm for automatic drawing of biochemical networks Reviewed

Li W., Kurata H.

Bioinformatics 21 ( 9 ) 2036 - 2042 2005.05

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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A Grid Layout Algorithm for Automatic Drawing of Biochemical Networks Reviewed

Weijiang Li,Hiroyuki Kurata

Bioinformatics 21 2036 - 2042 2005.04

有用物質生産のための細胞設計工学 Reviewed

倉田博之

ケミカルエンジニヤリング 50 907 - 912 2005.04

Surviving heat shock: Control strategy for robustness and performance Reviewed

H. El-Samad,H. Kurata,J.C. Doyle,C. A. Gross,M. Khammash

Proc Natl Acad Sci U S A. 102 2736 - 2741 2005.04

CADLIVE Dynamic Simulator: Direct Link of Biochemical Networks to Dynamic Models Reviewed

Hiroyuki Kurata,Kouichi Masaki,Yoshiyuki Sumida,Rei Iwasaki

Genome Res. 15 590 - 600 2005.04

A large-scale dynamic simulation of the cell cycle network Reviewed

Yamamichi,S.,Kurata,H.

Proceedings of 7th Asia-Pacific Biochemical Engineering Conference SYS2 - 05 2005.04

Module Decomposition and Integration Optimizes Gene Regulatory and Metabolic Networks

Keisuke Yoshida,Hiroyuki Kurata

The 16th International Conference on Genome Informatics 16 P123-1-2 2005.04

Interlocked Feedback is not the Best Choice for PER Oscillators

Fumitaka Ohnishi,Hiroyuki Kurata

The 16th International Conference on Genome Informatics 16 P116-1-2 2005.04

CADLIVE: Computer-Aided Design of Living Systems

Hiroyuki Kurata,Marie Kajiwara,Yuki Shimokawa

The 16th International Conference on Genome Informatics 16 P114-1-1 2005.04

Optimization of a Large-Scale Dynamic Model of the Cell Cycle Network Using Multi Objective GA

Shunsuke Yamamichi,Hiroyuki Kurata

The 16th International Conference on Genome Informatics 16 P122-1-2 2005.04

CADLIVE dynamic simulator: Direct link of biochemical networks to dynamic models Reviewed

Kurata H., Masaki K., Sumida Y., Iwasaki R.

Genome Research 15 ( 4 ) 590 - 600 2005.04

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Surviving heat shock: Control strategies for robustness and performance Reviewed

El-Samad H., Kurata H., Doyle J., Gross C., Khammash M.

Proceedings of the National Academy of Sciences of the United States of America 102 ( 8 ) 2736 - 2741 2005.02

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Optimization of E.Coli heat shock response parameter tuning using distributed and integrated genetic algorithms Reviewed

Tanaka S., Kurata H., Ohashi T.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 2 1243 - 1248 2004.12

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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.

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モジュール分割統合法による大規模生命分子ネットワークの最適化

吉田圭介,倉田博之

数理モデル化と問題解決シンポジウム論文集 97 - 102 2004.10

生命における振動システムのモデリングとシステム解析

山道俊介，大西史高，倉田博之

数理モデル化と問題解決シンポジウム論文集 379 - 382 2004.10

Computer-Aided Design of Metabolic and Gene Regulatory Networks Reviewed

Proceedings of The 10th APCChE Congress 2L - 06 2004.10

Optimization of E.Coli Heat Shock Response Parameter Tuning Using Distributed and Integrated Genetic Algorithms Reviewed

Shin Tanaka,Hiroyuki Kurata,Takeshi Ohashi

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 1243 - 1248 2004.10

Statistical And Integrative Approach For Constructing Biological Network Maps Reviewed

Hiroyuki Kurata,Natsumi Shimizu,Kanako Misumi

Genome Informatics 15 161 - 170 2004.04

Optimization and System Analysis of the Heat Shock Response by CADLIVE

Kouji Mitsukiyo,Marie Kajiwara,Hiroyuki Kurata

Genome Informatics Series 15 P006 2004.04

Simulation of Circadian Rhythms Using Grid Computing

Takayuki Tanaka,Hiroyuki Kurata

Genome Informatics Series 15 P011 2004.04

A Large-Scale Dynamic Model of the Yeast Cell Cycle

Shunsuke Yamamichi,Hiroyuki Kurata

Genome Informatics Series 15 P007 2004.04

CADLIVE: New Modules for Domain Expansions and Topological Analysis

Hiroyuki Kurata,Yuki Shimokawa,Tomoko Noguchi,Natsumi Shimizu

Genome Informatics Series 15 S05 2004.04

Statistical and Integrative Approach for Constructing Biological Network Maps Reviewed

Kurata Hiroyuki, Shimizu Natsumi, Misumi Kanako

Genome Informatics 15 ( 2 ) 161 - 170 2004.01

Statistical and integrative approach for constructing biological network maps. Reviewed

Kurata H., Shimizu N., Misumi K.

Genome informatics. International Conference on Genome Informatics 15 ( 2 ) 161 - 170 2004.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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.

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Computer-Aided Design of Metabolic and Gene Regulatory Networks Reviewed

Kurata Hiroyuki

アジア・太平洋化学工学会議発表論文要旨集 2004 ( 0 ) 419 - 419 2004.01

Integration of Postgenomic Data for GMA to Simulate a Metabolic Circuit

Takayuki Tanaka,Hiroyuki Kurata

Genome Informatics Series ( 14 ) 613 - 614 2003.12

CADLIVE SYSTEM: Map-based dynamic simulation of biochemical networks. Genome Informatics Series

Hiroyuki Kurata,Rei Iwasaki,Kouichi Masaki,Takayuki Tanaka,Kouji Mitsukiyo,Yoshiyuki Sumida

Genome Informatics Series ( 14 ) 270 - 271 2003.12

CADLIVE Automatic Visualizing System for Large-Scale Biochemical Maps

Weijiang Li,Hiroyuki Kurata

Genome Informatics Series ( 14 ) 388 - 389 2003.12

CADLIVE-Based Analysis for the Budding Yeast Cell Cycle

Natsumi Shimizu,Shunsuke Yamamichi,Hiroyuki Kurata

Genome Informatics Series ( 14 ) 609 - 610 2003.12

Deterministic and Stochastic Models Analyze the Robustness of Circadian Rhythms

Yoshiyuki Sumida,Fumitaka Ohnishi,Hiroyuki Kurata

Genome Informatics Series ( 14 ) 611 - 612 2003.12

Verification of the optimization performance of Real-Corded Genetic Algorithm with Dominant Direction Priority Searching Method Reviewed

TANAKA Shin, KURATA Hiroyuki, OHASHI Takeshi

IPSJ SIG Notes ( Information Processing Society of Japan (IPSJ) ) 47 49 - 52 2003.12

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

Real-Corded 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 Hybrid Genetic Algorithm (gradient GA) to use a gradient shows high optimization performance. But we cannot apply gradient GA for the optimization problem that it is impossible to calculate a gradient value of fitness function. So Dominant Direction Priority search method (DDP Searching Method) is suggested in order to reduce these problems. In DDP Searching method, we suppose a vector facing a superior gene from an inferior gene in population to be an indirect gradient direction (a dominant direction) And we carry out prior local search of dominant direction and GA crossover simultaneously. In this paper, we inspected the optimization performance in some mathematical benchmark functions and gene regulatory network simulation using DDP Searching Method.

CiNii Article

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Dominant direction priority searching method for real-corded genetic algorithm Reviewed

Shin T., Hiroyuki K., Takeshi O.

Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications 3 1113 - 1119 2003.12

Authorship：Corresponding author Publishing type：Research paper (international conference proceedings)

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.

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CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle Reviewed

Kurata H., Matoba N., Shimizu N.

Nucleic Acids Research 31 ( 14 ) 4071 - 4084 2003.07

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle Reviewed

H. Kurata,N. Matoba,N. Shimizu

Nucleic Acids Res. 31 4071 - 4084 2003.07

代謝シュミレーションの新展開 Reviewed

倉田博之

生物工学会誌 : seibutsu-kogaku kaishi 81 ( 6 ) 2003.06

Dominant Direction Priority Searching Method for Real-Corded Genetic Algorithm Reviewed

TANAKA Shin, KURATA Hiroyuki, OHASHI Takeshi

IPSJ SIG Notes ( Information Processing Society of Japan (IPSJ) ) 45 9 - 12 2003.06

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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. GA+DDP showed the effectiveness in optimization problems of mathematical function and gene regulatory network simulation.

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/110002914201

Dominant direction priority searching method for real-coded genetic algorithm Reviewed

Shin Tanaka,Hiroyuki Kurata,Ken Ohashi

Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications PDPTA'03 1113 - 1119 2003.06

Feedback Regulation of the Heat Shock Response in E. coli Reviewed

Hana El-Samad,Mustafa Khammash,Hiroyuki Kurata,John C. Doyle

Lecture Notes in Control and Information Sciences 289 115 - 128 2003.04

Deterministic and Stochastic Models Analyze the Robustness of Circadian Rhythms Reviewed

Sumida Yoshiyuki, Ohnishi Fumitaka, Kurata Hiroyuki

Genome Informatics 14 611 - 612 2003.01

CADLIVE-Based Analysis for the Budding Yeast Cell Cycle Reviewed

Shimizu Natsumi, Yamamichi Shunsuke, Kurata Hiroyuki

Genome Informatics 14 609 - 610 2003.01

CADLIVE Automatic Visualizing System for Large-Scale Biochemical Maps Reviewed

Li Weijiang, Kurata Hiroyuki

Genome Informatics 14 388 - 389 2003.01

Building common patterns of transcription factor binding sites of Escherichia coli

W. Li,H. Kurata

Genome Informatics Series 13 301 - 302 2002.12

SANAC: Mathematical simulator for elucidating the architecture of biochemical networks

H. Kurata,H. Kitano

Genome Informatics Series 13 242 - 243 2002.12

BIOCAD project for synthesis and analysis of gene regulatory networks

Hiroyuki Kurata,Yoshiyuki Sumida,Shin Tanaka,Kouichi Masaki,Takayuki Tanaka,Yuki Urago,Ken Ohashi

Genome Informatics Series 13 467 - 477 2002.12

Screening for transgenic plant cells that highly express a target gene from genetically mixed cells Reviewed

H. Akashi,H.Kurata,M. Seki,K. Taira,S. Furusaki

Biochem. Eng. J. 10 175 - 182 2002.07

Robustness Analysis of the heat shock response in E. coli Reviewed

H. El-Samad,M. Khammash,H. Kurata,H. T.-M. Yi,J. C. Doyle

Proceedings of the 2002 American Control Conference 1742 - 1747 2002.05

Screening for transgenic plant cells that highly express a target gene from genetically mixed cells Reviewed

Akashi H., Kurata H., Seki M., Taira K., Furusaki S.

Biochemical Engineering Journal 10 ( 3 ) 175 - 182 2002.04

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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BIOCAD Project for Synthesis and Analysis of Gene Regulatory Networks Reviewed

Kurata Hiroyuki, Sumida Yoshiyuki, Tanaka Shin, Masaki Kouichi, Tanaka Takayuki, Urago Yuki, Ohashi Ken

Genome Informatics 13 467 - 468 2002.01

Building Common Patterns for Transcription Factor Binding Sites of Escherichia coli Reviewed

Li Weijiang, Kurata Hiroyuki

Genome Informatics 13 301 - 302 2002.01

Robustness analysis of the heat shock response in E. coli Reviewed

El-Samad H., Khammash M., Kurata H., Doyle J.

Proceedings of the American Control Conference 3 1742 - 1747 2002.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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

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BIOCAD project for constructing a biological system in silico

T.Adachi,N. Matoba,H. Kurata

Genome Informatics Series 12 284 - 285 2001.12

Simulation and system analysis of gene regulatory networks using the two-phase partition method

H. Kurata,T. Inoue,Y. Sumida,S. Tanaka,T. Ohashi

Genome Informatics Series 286 - 287 2001.12

Feedback regulation of the heat shock response in E. coli Reviewed

H. Kurata,H. El-Samad,T.-M. Yi,M. Khammash,J. C. Doyle

Proceedings of the 40th IEEE Conference on Decision and Control 837 - 842 2001.12

A simple and rapid system for the quantitation of RNA interference in plant cultured cells Reviewed

Akashi H,Miyagishi M,Kurata H,Nagata T,Taira K.

Nucleic Acids Res. Suppl. ( 1 ) 235 - 236 2001.01

BIOCAD Project for Constructing a Biological System in Silico Reviewed

Adachi Tadashi, Matoba Nana, Kurata Hiroyuki

Genome Informatics 12 284 - 285 2001.01

A simple and rapid system for the quantitation of RNA interference in plant cultured cells. Reviewed

Akashi H., Miyagishi M., Kurata H., Nagata T., Taira K.

Nucleic acids research. Supplement (2001) ( 1 ) 235 - 236 2001.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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

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Glucocorticoid-induced expression of a foreign gene by the GVG system in transformed tobacco BY-2 cells Reviewed

Nara Y., Kurata H., Seki M., Taira K.

Biochemical Engineering Journal 6 ( 3 ) 185 - 191 2000.12

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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MAXIZYMEs: Allosterically controllable ribozymes with biosensor functions Reviewed

Kurata H., Miyagishi M., Kuwabara T., Warashina M., Taira K.

Journal of Biochemistry and Molecular Biology 33 ( 5 ) 359 - 365 2000.09

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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.

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Intermittent light irradiation with second- or hour-scale periods controls anthocyanin production by strawberry cells Reviewed

Kurata H., Mochizuki A., Okuda N., Seki M., Furusaki S.

Enzyme and Microbial Technology 26 ( 8 ) 621 - 629 2000.05

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Intermittent light irradiation with second- or hour- scale periods controls anthocyanin production by strawberry cells Reviewed

Kurata H.,Mochizuki A.,Okuda N.,Seki M.,Furusaki S.

Enzyme Microb. Technol. 26 ( # ) 621 - 629 2000.04

Grucocorticoid-induced expression of a foreign gene by the GVG system in transformed tobacco BY-2 Reviewed

Nara Y.,Kurata H.,Seki M,Taira K.

Biochem. Eng. J. 6 ( # ) 185 - 191 2000.04

Two-phase partition method for simulating a biological system at an extremely high speed Reviewed

Kurata H.,Taira K.

Genome Informatics 11 ( # ) 185195 - 185195 2000.04

Complexity in Regulation Generates Robustness in Bacterial Molecular Networks

Kurata H.,Taira K.

Proceedings of the First International Conference on Systems Biology 1 ( # ) 167 - 172 2000.04

Evolution of Ammonia Assimilation System in E. coli. ,17-24.

Kurata H.,Taira K.

Technical Report of IEICE AI2000-12 ( # ) 17 - 24 2000.04

Two-Phase Partition Method for Simulating a Biological System at an Extremely High Speed Reviewed

Kurata Hiroyuki, Taira Kazunari

Genome Informatics 11 185 - 195 2000.01

Two-phase partition method for simulating a biological system at an extremely high speed. Reviewed

Kurata H., Taira K.

Genome informatics. Workshop on Genome Informatics 11 185 - 195 2000.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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.

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Mathematical model analyzes light-controlled expression of the CHS promoter in BY-2 cells Reviewed

Kurata H., Kaizuka Y., Seki M., Furusaki S.

Biochemical Engineering Journal 4 ( 1 ) 65 - 72 1999.09

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Software of living systems Reviewed

Ohtake H., Tsuji T., Kurata H.

Kagaku Kogaku Ronbunshu 25 ( 2 ) 174 - 176 1999.03

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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.

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Intermittent light irradiation with a second-scale interval enhances caffeine production by Coffea arabica cells Reviewed

Kurata H., Achioku T., Okuda N., Furusaki S.

Biotechnology Progress 14 ( 5 ) 797 - 799 1998.09

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Light enhanced target gene expression in tobacco BY-2 by the combination of overexpressed phytochrome and rbcS3A promoter Reviewed

Kurata H., Furusaki S., Kado C.

Biotechnology Letters 20 ( 5 ) 463 - 468 1998.07

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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The light/dark cycle operation with an hour-scale period enhances caffeine production by Coffea arabica cells Reviewed

Kurata H., Achioku T., Furusaki S.

Enzyme and Microbial Technology 23 ( 7-8 ) 518 - 523 1998.01

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Light-controlled expression of a foreign gene using the chalcone synthase promoter in tobacco BY-2 cells Reviewed

Kurata H., Takemura T., Furusaki S., Kado C.

Journal of Fermentation and Bioengineering 86 ( 3 ) 317 - 323 1998.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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

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Light irradiation causes physiological and metabolic changes for purine alkaloid production by a Coffea arabica cell suspension culture Reviewed

Kurata H., Matsumura S., Furusaki S.

Plant Science 123 ( 1-2 ) 197 - 203 1997.03

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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

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Increased alkaloid production in a suspension culture of Coffea arabica cells using an adsorption column for product removal Reviewed

Kurata H., Kawai A., Seki M., Furusaki S.

Journal of Fermentation and Bioengineering 78 ( 1 ) 117 - 119 1994.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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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Immobilized Coffea arabica cell culture using a bubble‐column reactor with controlled light intensity Reviewed

Kurata H., Furusaki S.

Biotechnology and Bioengineering 42 ( 4 ) 494 - 502 1993.08

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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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Nonisotropic Scattering Model for Estimation of Light Absorption Rates in a Suspension Culture of Coffea arabica Cells Reviewed

Kurata H., Furusaki S.

Biotechnology Progress 9 ( 1 ) 86 - 92 1993.01

Authorship：Corresponding author Publishing type：Research paper (scientific journal)

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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Influence of light irradiation rates and irradiation modes on caffeine production and cell growth in suspension culture of coffea arabica cells Reviewed

Kurata H., Seki M., Furusaki S., Furuya T.

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 24 ( 6 ) 783 - 788 1991.01

Authorship：Corresponding author Language：English Publishing type：Research paper (scientific journal)

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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Effect of Light on Caffeine Production by Plant Cells of Coffea arabicaa Reviewed

KURATA H., SEKI M., FURUSAKI S., FURUYA T.

Annals of the New York Academy of Sciences 613 ( 1 ) 538 - 541 1990.12

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