矢田 哲士 (ヤダ テツシ)

YADA Tetsushi

写真a

職名

教授

研究室住所

福岡県飯塚市川津680-4

研究分野・キーワード

バイオインフォマティクス、ゲノム生物学

出身大学 【 表示 / 非表示

  • 1988年03月   九州大学   理学部   生物学科   卒業   日本国

取得学位 【 表示 / 非表示

  • 東京大学 -  博士(理学)  1998年06月

学内職務経歴 【 表示 / 非表示

  • 2019年04月
    -
    継続中

    九州工業大学   大学院情報工学研究院   生命化学情報工学研究系   教授  

  • 2017年04月
    -
    2018年03月

    九州工業大学   情報工学部   情報工学部生命情報工学科長  

  • 2017年04月
    -
    2018年03月

    九州工業大学   大学院情報工学府   情報工学府学際情報工学専攻長・情報システム専攻長  

  • 2017年04月
    -
    2018年03月

    九州工業大学   大学院情報工学府   情報工学府情報工学専攻長  

  • 2017年04月
    -
    2018年03月

    九州工業大学   大学院情報工学研究院   情報工学研究院生命情報工学研究系長  

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学外略歴 【 表示 / 非表示

  • 2007年04月
    -
    2013年04月

    京都大学   大学院情報学研究科   准教授   日本国

  • 2003年10月
    -
    2007年03月

    京都大学   大学院情報学研究科   助教授   日本国

  • 2001年04月
    -
    2003年09月

    東京大学   医科学研究所   助教授   日本国

  • 1999年04月
    -
    2001年03月

    理化学研究所   ゲノム科学総合研究センター   研究員   日本国

  • 1988年04月
    -
    1999年03月

    株式会社三菱総合研究所   研究員   日本国

 

論文 【 表示 / 非表示

  • Genome sequence alignment

    Tetsushi Yada

    Encyclopedia of Bioinformatics and Computational Biology      2018年09月  [査読有り]  [招待有り]

  • Asymmetry in indegree and outdegree distributions of gene regulatory networks arising from dynamical robustness

    Ichinose N., Yada T., Wada H.

    Physical Review E    97 ( 6 )   2018年06月  [査読有り]

     概要を見る

    © 2018 American Physical Society. Although outdegree distributions of gene regulatory networks have scale-free characteristics similar to other biological networks, indegree distributions have single-scale characteristics with significantly lower variance than that of outdegree distributions. In this study, we mathematically explain that such asymmetric characteristics arise from dynamical robustness, which is the property of maintaining an equilibrium state of gene expressions against inevitable perturbations to the networks, such as gene dysfunction and mutation of promoters. We reveal that the expression of a single gene is robust to a perturbation for a large number of inputs and a small number of outputs. Applying these results to the networks, we also show that an equilibrium state of the networks is robust if the variance of the indegree distribution is low (i.e., single-scale characteristics) and that of the outdegree distribution is high (i.e., scale-free characteristics). These asymmetric characteristics are conserved across a wide range of species, from bacteria to humans.

    DOI Scopus

  • Micropeptides encoded in transcripts previously identified as long noncoding RNAs: A new chapter in transcriptomics and proteomics

    Yeasmin F., Yada T., Akimitsu N.

    Frontiers in Genetics    9 ( APR )   2018年04月  [査読有り]

     概要を見る

    © 2018 Yeasmin, Yada and Akimitsu. Integrative analysis using omics-based technologies results in the identification of a large number of putative short open reading frames (sORFs) with protein-coding capacity within transcripts previously identified as long noncoding RNAs (lncRNAs) or transcripts of unknown function (TUFs). sORFs were previously overlooked because of their diminutive size and the difficulty of identification by bioinformatics analyses. There is now growing evidence of the existence of potentially functional micropeptides produced from sORFs within cells of diverse species. Recent characterization of a few of these revealed their significant divergent roles in many fundamental biological processes, where some also show important relationships with pathogenesis. Recent works therefore provide new insights for exploring the wealth of information that may lie within sORF-encoded short proteins. Here, we summarize the current progress and view of micropeptides encoded in sORFs of protein-coding genes.

    DOI Scopus

  • A new computational method to predict transcriptional activity of a DNA sequence from diverse datasets of massively parallel reporter assays

    Liu Y., Irie T., Yada T., Suzuki Y.

    Nucleic Acids Research    45 ( 13 )   2017年07月  [査読有り]

     概要を見る

    © 2017 The Author(s). In recent years, the dramatic increase in the number of applications for massively parallel reporter assay (MPRA) technology has produced a large body of data for various purposes. However, a computational model that can be applied to decipher regulatory codes for diverse MPRAs does not exist yet. Here, we propose a new computational method to predict the transcriptional activity of MPRAs, as well as luciferase reporter assays, based on the TRANScription FACtor database. We employed regression trees and multivariate adaptive regression splines to obtain these predictions and considered a feature redundancy-dependent formula for conventional regression trees to enable adaptation to diverse data. The developed method was applicable to various MPRAs despite the use of different types of transfected cells, sequence lengths, construct numbers and sequence types. We demonstrate that this method can predict the transcriptional activity of promoters in HEK293 cells through predictive functions that were estimated by independent assays in eight tumor cell lines. The prediction was generally good (Pearson’s r = 0.68) which suggested that common active transcription factor binding sites across different cell types make greater contributions to transcriptional activity and that known promoter activity could confer transcriptional activity of unknown promoters in some instances, regardless of cell type.

    DOI Scopus

  • Estimating optimal sparseness of developmental gene networks using a semiquantitative model'

    Ichinose N., Yada T., Wada H.

    PLoS ONE    12 ( 4 )   2017年04月  [査読有り]

     概要を見る

    © 2017 Ichinose et al. To estimate gene regulatory networks, it is important that we know the number of connections, or sparseness of the networks. It can be expected that the robustness to perturbations is one of the factors determining the sparseness. We reconstruct a semi-quantitative model of gene networks from gene expression data in embryonic development and detect the optimal sparseness against perturbations. The dense networks are robust to connectionremoval perturbation, whereas the sparse networks are robust to misexpression perturbation. We show that there is an optimal sparseness that serves as a trade-off between these perturbations, in agreement with the optimal result of validation for testing data. These results suggest that the robustness to the two types of perturbations determines the sparseness of gene networks.

    DOI Scopus

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科研費獲得実績 【 表示 / 非表示

  • 次世代シークエンサー解析と情報科学解析で迫る転写調節コードの普遍性と多様性

    新学術領域研究

    研究期間:  2015年04月  -  2017年03月

    研究課題番号:  15H01358

  • プロモーター配列の情報科学的解体と再構成による遺伝子回路の設計

    新学術領域研究

    研究期間:  2014年04月  -  2016年03月

    研究課題番号:  26119717

  • 遺伝子のde novo誕生の機序に迫るバイオインフォマティクス研究

    挑戦的萌芽研究

    研究期間:  2013年04月  -  2016年03月

    研究課題番号:  25640112

 

担当授業科目 【 表示 / 非表示

  • 2018年度  科学技術英語Ⅱ

  • 2018年度  データベースB

  • 2018年度  解析Ⅰ・同演習

  • 2018年度  学際情報講究Ⅲ

  • 2018年度  卒業研究

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