Curriculum Vitae

[English   Japanese]

Personal Details:

Name:Yoshihiro Yamanishi
Status:Male
Date of Birth:October 6, 1976
Nationality:Japan
ORCID:https://orcid.org/0000-0003-2279-8773
Google Scholar ID:y9Qo1t7ha0sC
Semantic Scholar ID:34724293
DBLP ID:87/1818

Affiliation:

Affiliation   Department of Complex Systems Science,
Graduate School of Informatics,
Nagoya University
Address Chikusa, Nagoya 464-8601, JAPAN
Tel +81-52-789-5638
Physical office Informatics Research Building, Room 808
E-mail yamanishi@
URL https://yamanishi.cs.i.nagoya-u.ac.jp/
(Please replace "@" by "@i.nagoya-u.ac.jp")

Experience:

2023.4 - present    Professor at Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Japan
2019.11 - 2020.11    Visiting Professor at School of Physical and Mathematical Sciences, Nanyang Technological University (NTU)), Singapore
2018.6 - 2023.3    Professor at Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Japan
2015.10 - 2019.3    PRESTO researcher, JST, Japan
2012.3 - 2018.5    Associate Professor at Division of System Cohort, Medical Institute of Bioregulation, Kyushu University, Japan
2012.3 - 2017.2    Associate Professor at Institute for Advanced Study, Kyushu University, Japan
2008.1 - 2012.2    Permanent Researcher at Unit of Bioinformatics, Biostatistics, Epidemiology and Computational Systems Biology of Cancer, Curie Institute, France
2008.1 - 2012.2    Permanent Researcher at Center for Computational Biology, Mines ParisTech, France
2006.4 - 2007.12    Assistant Professor at Institute for Chemical Research, Kyoto University, Japan
2005.4 - 2006.3    Postdoctral Fellow at Center for Computational Biology, École Nationale Supérieure des Mines, France
2004.4 - 2005.3    Research Fellow of the Japan Society for the Promotion of Science (DC2), Japan

Academic degree:

2005.3.23    Ph.D., Doctor of Science, Kyoto University, Japan
      "Development of methods for analyzing heterogeneous genomic data and for inferring protein networks", Doctoral Thesis, Graduate School of Science, Kyoto University

Award:

2021.7.9    Tanabe Prize, The Japanese Society of Toxicology
2014.4.7    The Young Scientists’ Prize, The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology
2003.12.5    The ICR Award for Students (ICR: Institute for Chemical Research, Kyoto University)

Social activity:

2024.1-present    International Society for Computational Biology (ISCB), Board of Directors
2023.4-present    Japan Bioinformatics Society (JSBi), President
2021.4-2023.3    Japan Bioinformatics Society (JSBi), Vice-president
2016.4-present    Japan Bioinformatics Society (JSBi), Executive board member
2018.4-2023.3    Division of Chemoinformatics, The Chemical Society of Japan (CICSJ), Executive board member
2018.4-present    Japan Medical AI Society (JMAI), Councilor
2024.2-present    Artificial Intelligence in the Life Sciences, Editorial Board
2023.8-2026.8    Bioinformatics Advances, Editorial Board (Associate Editor)
2021.4-2023.3    Journal of Computer Aided Chemistry, Editorial board (Associate Editor)
2019.7-present    F1000Research Chemical Information Science Gateway, Advisory Board
2017.1-present    Molecular Informatics, Editorial board (Associate Editor)
2016.7-2024.3    Genes & Genetic Systems, Editorial board (Associate Editor)
2014.12-2018.8    BioMed International, Editorial board (Associate Editor)
2013.6-present    PLoS ONE, Editorial board (Associate Editor)

Academic society:

   Japanese Society for Bioinformatics (JSBi)
   The Chem-Bio Informatics Society (CBI)
   Japanese Society of Computational Statistics (JSCS)
   Division of Chemoinformatics, The Chemical Society of Japan (CICSJ)
   Japan Medical AI Society (JMAI)
   International Society for Computational Biology (ISCB)

Research Interests:

Publications:

ISMB/ECCB Oral Presentations:

  1. Nakamura, T., Iwata, M., Hamano, M., Eguchi, R., Takeshita, J., and Yamanishi, Y,
    "Small compound-based direct cell conversion with combinatorial optimization of pathway regulations",
    The 21st European Conference on Computational Biology (ECCB2022), Barcelona, Spain, Sep.18-Sep.21, 2022
  2. Namba, S., Iwata, M., and Yamanishi, Y,
    "From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures",
    The 30th International Conference on Intelligent Systems for Molecular Biology (ISMB2022), Madison, USA, Jul.10-Jul.14, 2022
  3. Iida, M., Iwata, M., and Yamanishi, Y.,
    "Network-based characterization of disease–disease relationships in terms of drugs and therapeutic targets",
    The 28th International Conference on Intelligent Systems for Molecular Biology (ISMB2020), Online, Jul.13-Jul.16, 2020
  4. Iwata, M., Yuan, L., Zhao, Q., Tabei, Y., Berenger, F., Sawada, R., Akiyoshi, S., Hamano, M., and Yamanishi, Y.,
    "Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm",
    The 27th International Conference on Intelligent Systems for Molecular Biology & 18th European Conference on Computational Biology (ISMB/ECCB2019), Basel, Switzerland, Jul.21-Jul.25, 2019
  5. Tabei, Y., Yamanishi, Y., and Kotera, M.,
    "Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction",
    The 24th International Conference on Intelligent Systems for Molecular Biology (ISMB2016), Orlando, Florida, USA, Jul.8-Jul.12, 2016.
  6. Yamanishi, Y., Tabei, Y., and Kotera, M.,
    "Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments",
    The 23rd International Conference on Intelligent Systems for Molecular Biology & 14th European Conference on Computational Biology (ISMB/ECCB2015), Dublin, Ireland, Jul.10-Jul.14, 2015.
  7. Kotera, M., Tabei, Y., Yamanishi, Y., Muto, A., Moriya, Y., Tokimatsu, T., and Goto, S.,
    "Metabolome-scale prediction of intermediate compounds in multi-step metabolic pathways with a recursive supervised approach",
    The 22nd International Conference on Intelligent Systems for Molecular Biology (ISMB2014), Boston, USA, Jul.11-Jul.15, 2014.
  8. Kotera, M., Tabei, Y., Yamanishi, Y., Tokimatsu, T., and Goto, S.,
    "Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets",
    The 21st International Conference on Intelligent Systems for Molecular Biology & 12th European Conference on Computational Biology (ISMB/ECCB2013), Berlin, Germany, Jul.19-Jul.23, 2013.
  9. Takarabe, M., Kotera, M., Nishimura, Y., Goto, S., and Yamanishi, Y.,
    "Drug target prediction using adverse event report systems: a pharmacogenomic approach",
    The 11th European Conference on Computational Biology (ECCB2012), Basel, Switzerland, Sep.9-Sep.12, 2012.
  10. Mizutani, S., Pauwels, E., Stoven, V., Goto, S., and Yamanishi, Y.,
    "Relating drug-protein interaction network with drug side-effects",
    The 11th European Conference on Computational Biology (ECCB2012), Basel, Switzerland, Sep.9-Sep.12, 2012.
  11. Tabei, Y., Pauwels, E., Stoven, V., Takemoto, K., and Yamanishi, Y.,
    "Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers",
    The 11th European Conference on Computational Biology (ECCB2012), Basel, Switzerland, Sep.9-Sep.12, 2012.
  12. Yamanishi, Y., Kotera, M., Kanehisa, M., and Goto, S.,
    "Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework",
    The 18th International Conference on Intelligent Systems for Molecular Biology (ISMB2010), Bonston, USA, Jul.8-Jul.13, 2010.
  13. Yamanishi, Y., Hattori, M., Kotera, M., Goto, S., and Kanehisa, M.,
    "E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs",
    The 17th International Conference on Intelligent Systems for Molecular Biology & 8th European Conference on Computational Biology (ISMB/ECCB2009), Stockholm, Sweden, Jun.27-Jul.2, 2009.
  14. Yamanishi, Y., Araki, M., Gutteridge, A., Honda, W., and Kanehisa, M.,
    "Prediction of drug-target interaction networks from the integration of chemical and genomic spaces",
    The 16th International Conference on Intelligent Systems for Molecular Biology (ISMB2008), Toronto, Canada, Jun.20-Jun.23, 2008.
  15. Yamanishi, Y., Vert, J.-P. and Kanehisa, M.,
    "Supervised Enzyme Network Inference from the Integration of Genomic Data and Chemical Information",
    The 13th International Conference on Intelligent Systems for Molecular Biology (ISMB2005), Detroit, USA, Jun.26-Jun.29, 2005.
  16. Yamanishi, Y., Vert, J.-P. and Kanehisa, M.,
    "Protein Network Inference from Multiple Genomic Data: A Supervised Approach",
    The 12th International Conference on Intelligent Systems for Molecular Biology (ISMB2004), Glasgow, Scotland, Jul.31-Aug.4, 2004.
  17. Yamanishi, Y., Vert, J.-P., Nakaya, A. and Kanehisa, M.,
    "Extraction of Correlated Gene Clusters from Multiple Genomic Data by Generalized Kernel Canonical Correlation Analysis",
    The 11th International Conference on Intelligent Systems for Molecular Biology (ISMB2003), Brisbane, Australia, Jun.29-Jul.3, 2003.

Invited talks at international conferences:

  1. Yamanishi, Y.,
    "Data-driven drug discovery and healthcare by machine learning",
    The 14th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB2024) (ICBBB2024), Kyoto, Japan, Jan.12-Nov.15 (presentation on Jan. 14), 2024. [Keynote invited talk]
  2. Yamanishi, Y.,
    "Data-driven drug discovery and healthcare by machine learning",
    International Workshop on Data-driven Science for Graphs: Algorithms, Architectures, and Applications (IEEE BigData) (IEEE BigData), Sorrento, Italy, Dec.15-Dec.17 (presentation on Dec. 17), 2023. [Keynote invited talk]
  3. Yamanishi, Y.,
    "Data-driven drug discovery and healthcare by machine learning",
    The 13th International Workshop on Biomedical and Health Informatics (BHI2023) (IEEE BIBM), Istanbul, Turkey, Dec.5-Dec.8 (presentation on Dec. 7), 2023. [Keynote invited talk]
  4. Yamanishi, Y.,
    "Data-driven drug discovery and healthcare by machine learning",
    The 8th Autumn School of Chemoinformatics in Nara 2023 (HP), Nara, Japan, Nov.28-Nov.30 (presentation on Nov. 29), 2023. [Invited talk]
  5. Yamanishi, Y.,
    "Data-driven drug discovery and healthcare by machine learning",
    The 3rd International Conference on Image, Vision and Intelligent Systems (ICIVIS2023) (ICIVIS2023), Baoding, Chaina, Aug.16-Aug.18 (presentation on Aug. 17), 2023. [Invited talk]
  6. Yamanishi, Y.,
    "Data-driven drug discovery and molecular design by machine learning",
    Inserm/JSPS joint seminar on artificial intelligence and big data approaches in precision medicine and health science (HP), Yamaguchi, Japan, Dec.3-Dec.4 (presentation on Dec. 4), 2022. [Invited talk]
  7. Yamanishi, Y.,
    "Data-driven drug discovery and molecular design by machine learning",
    The 7th Autumn School of Chemoinformatics in Nara 2022 (HP), Nara, Japan, Nov.29-Nov.30 (presentation on Nov. 29), 2022. [Invited talk]
  8. Yamanishi, Y.,
    "Data-driven drug discovery and medical treatment by machine learning",
    The Eighteenth International Conference on Intelligent Computing (ICIC2022), Xi'an, China, Aug.7-Aug.11 (presentation date: Aug. 9), 2022. [Invited talk]
  9. Yamanishi, Y.,
    "Network-based and data-driven drug discovery by machine learning",
    BioNetVisA workshop at the 20th International Conference on Systems Biology (ICSB2019), Okinawa, Japan, Oct.31, 2019. [Invited talk]
  10. Yamanishi, Y.,
    "Data-driven drug discovery and medical treatment by machine learning",
    ACS Fall 2019 National Meeting & Exposition, Herman Skolnik Symposium, San Diego, USA, Aug.27-Aug.27, 2019. [Invited talk]
  11. Yamanishi, Y.,
    "Machine learning approach to bioinformatics and drug discovery"",
    2019 Gorden Research Conference (GRC), (HP), Lucca (Barga), Italy, Mar.10-Mar.15, 2019. [Invited talk]
  12. Yamanishi, Y.,
    "Data-driven drug discovery and repositioning by machine learning methods",
    ACS Fall 2018 National Meeting & Exposition, Herman Skolnik Symposium, "De novo design - Automating drug discovery" session(HP), Boston, USA, Aug.21-Aug.21, 2018. [Invited talk]
  13. Yamanishi, Y.,
    "Data-driven drug discovery and repositioning by machine learning",
    The 5th Autumn School of Chemoinformatics in Nara 2017 (HP), Nara, Nov.15-Nov.16, 2017. [Invited talk]
  14. Yamanishi, Y.,
    "Statistical machine learning approaches for agriculture and human healthcare based on biomedical big data",
    Forum "Math-for-Industry" 2016 (FMfI2016), Brisbane, Australia, Nov.21-Nov.23, 2016. [Invited talk]
  15. Yamanishi, Y.,
    "Statistical machine learning for drug discovery",
    First Kyushu-UNSW Joint Workshop on the Mathematics underpinning Industry and Innovation, Sydney, Australia, Nov.18, 2016. [Invited talk]
  16. Yamanishi, Y.,
    "Systematic drug repositioning via omics data analysis with machine learning methods",
    Autumn School of Chemoinformatics in Tokyo (HP), Tokyo, Nov.25-Nov.26, 2015. [Invited talk]
  17. Yamanishi, Y.,
    "Systematic drug repositioning for a wide range of diseases with computational approaches",
    JCUP VI (JCUP VI), Tokyo, Jun.4-Jun.5, 2015. [Invited talk]
  18. Yamanishi, Y.,
    "Analysis and inference of drug-target interaction networks",
    International Symposium on Bioinformatics and its Application (ISBA), Tokyo, Japan, Sep.30, 2014. [Invited talk]
  19. Yamanishi, Y.,
    "Analysis and inference of drug-target interaction networks",
    The 2nd BMIRC International Symposium on Advances in Bioinformatics and Medical Engineering (BMIRC2014), Iizuka, Japan, Jan.29-Jan.30, 2014. [Invited talk]
  20. Yamanishi, Y.,
    "Predicting drug-target interaction networks from the integration of chemical, genomic, and pharmacological spaces",
    International Symposium on Tumor Biology in Kanazawa & Academic Drug Discovery Symposium (HP), Kanazawa, Japan, Jan.23-Jan.24, 2014. [Invited talk]
  21. Yamanishi, Y.,
    "Machine learning methods to analyze and infer drug-target interaction networks",
    2012 Sapporo Workshop on Machine Learning and Applications to Biology (MLAB2012), Sapporo, Japan, Aug.6-Aug.7, 2012. [Invited talk]
  22. Yamanishi, Y.,
    "Predicting drug-target interaction networks from the integration of chemical, genomic, and pharmacological spaces",
    The 2012 workshop on statistical methods for post-genomic data (SMPGD2012), Lyon, France, Jan.26-Jan.27, 2012. [Invited talk]
  23. Yamanishi, Y.,
    "Prediction of drug-target interactions from the integration of chemical, genomic and pharmacological data",
    Workshop on Bioinformatics for Medical and Pharmaceutical Research (website), Paris, France, Nov.16-Nov.17, 2009. [Invited talk]
  24. Yamanishi, Y.,
    "Supervised bipartite graph inference: applications to predicting drug-target interactions",
    The workshop on Statistic Mathematic and Applications, Frejus (La Villa Clythia), France, Sep.01-05, 2008. [Invited talk]
  25. Yamanishi, Y.,
    "Metabolic Network Inference from Multiple Types of Genomic Data",
    INRA Workshop on System Biology (INRA), Paris, France, Feb.2, 2006. [Invited talk]
Last updated: April 4, 2023
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