Kyushu University Academic Staff Educational and Research Activities Database
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Yoshihiro Yamanishi Last modified date:2016.05.26



Graduate School
Other Organization


E-Mail
Homepage
http://www.bioreg.kyushu-u.ac.jp/labo/systemcohort/index.html
Lab HP .
Phone
092-642-6932
Fax
092-642-6692
Academic Degree
Ph.D.
Field of Specialization
Bioinformatics
Outline Activities
Development of statistical methods for bioinformatics and their application to medical treatment and drug discovery
Research
Research Interests
  • Genomic drug discovery
    keyword : Prediction of drug-target interaction network, Identification of drug targets and off-targets, Prediction of drug side-effects, Analysis of adverse event report system, Chemogenomics, Pharmacogenomics, Drug repositioning
    2002.04~2017.03.
  • Systems biology
    keyword : Supervised inference of biological networks, Prediction of gene networks, Prediction of metabolic pathways, Prediction of protein-protein interaction networks, Prediction of protein-ligand interaction networks
    2002.04~2017.03.
  • Bioinformatics
    keyword : Identification of missing enzyme genes, Integration of heterogeneous omix data, Statistical analysis for gene expression data, Automatic construction of ortholog gene clusters, Glycan classification
    2002.04~2017.03.
  • Chemoinformatics
    keyword : Prediction of enzymatic reactions, Automatic assignment of EC numbers, Virtual screening, Compound classification, Similarity design for compounds and reactions
    2004.04~2017.03.
  • Statistics and Machine Learning
    keyword : Kernel methods, Graph inference, Sparse statistical models, Sensitivity analysis, Functional data analysis
    1999.04~2017.03.
Academic Activities
Books
1. Huma Lodhi and Yoshihiro Yamanishi, Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, IGI Global, 2010.07, [URL].
Papers
1. Sawada, R., Iwata, H., Mizutani, S., Yamanishi, Y., Target-based drug repositioning using large-scale chemical-protein interactome data, Journal of Chemical Information and Modeling, 55, 12, 2015.12.
2. Yamanishi, Y., Tabei, Y., Kotera, M., Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments, Bioinformatics, 31, 12, 2015.06.
3. Iwata, H., Sawada, R., Mizutani, S., Yamanishi, Y., Systematic drug repositioning for a wide range of diseases with integrative analyses of phenotypic and molecular data, Journal of Chemical Information and Modeling, 55, 2, 2015.01.
4. Yamanishi, Y., Kotera, M., Moriya, Y., Sawada, R., Kanehisa, M., Goto, S., DINIES: drug-target interaction network inference engine based on supervised analysis, Nucleic Acids Research, 42, 2014.06.
5. Yamanishi, Y., Pauwels, E., and Kotera, M., Drug side-effect prediction based on the integration of chemical and biological spaces, Journal of Chemical Information and Modeling, 52, 12, 3284-3292, 2012.12.
6. Takarabe, M., Kotera, M., Nishimura, Y., Goto, S., and Yamanishi, Y., Drug target prediction using adverse event report systems: a pharmacogenomic approach, Bioinformatics, 28, i611-i618, 2012.09.
7. Mizutani, S., Pauwels, E., Stoven, V., Goto, S., and Yamanishi, Y., Relating drug-protein interaction network with drug side-effects, Bioinformatics, 28, i522-i528, 2012.09.
8. Tabei, Y., Pauwels, E., Stoven, V., Takemoto, K., and Yamanishi, Y., Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers, Bioinformatics, 28, i487-i494, 2012.09.
9. Kotera, M., Yamanishi, Y., Moriya, Y., Kanehisa, M., Goto, S., GENIES: gene network inference engine based on supervised analysis, Nucleic Acids Research, 40, W162-W167, 2012.06.
10. Pauwels, E., Stoven, V., and Yamanishi, Y., Predicting drug side-effect profiles: a chemical fragment-based approach, BMC Bioinformatics, 12, 169, 2011.05.
11. Yamanishi, Y., Pauwels, E., Saigo, H. and Stoven, V., Extracting sets of chemical substructures and protein domains governing drug-target interactions, Journal of Chemical Information and Modeling, 51, 5, 1183-1194, 2011.05.
12. Yamanishi, Y., Kotera, M., Kanehisa, M., and Goto, S., Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework, Bioinformatics, 26, i246-i254, 2010.06.
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, Bioinformatics, 25, i79-i86, 2009.06.
14. Yamanishi, Y., Supervised Bipartite Graph Inference, Advances in Neural Information Processing Systems 21, 1841-1848, 2009.06.
15. 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, Bioinformatics, 24, i232-i240, 2008.06.
16. Yamanishi, Y., Bach, F., and Vert, J.-P., Glycan Classification with Tree Kernels, Bioinformatics, 23, 10, 1211-1216, 2007.05.
17. Yamanishi, Y., Mihara, H., Osaki, M., Muramatsu, H., Esaki, N., Sato, T., Hizukuri, Y., Goto, S., and Kanehisa, M., Prediction of missing enzyme genes in a bacterial metabolic network: Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa, FEBS Journal, 274, 2262-2273, 2007.05.
18. Yamanishi, Y., Vert, J.-P. and Kanehisa, M., Supervised Enzyme Network Inference from the Integration of Genomic Data and Chemical Information, Bioinformatics, 21, i468-i477, 2005.06.
19. Yamanishi, Y., Vert, J.-P. and Kanehisa, M., Protein Network Inference from Multiple Genomic Data: A Supervised Approach, Bioinformatics, 20, i363-i370, 2004.08.
20. 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, Bioinformatics, 19, i323-i330, 2003.06.
Works, Software and Database
1.
[URL].
2.
[URL].
3.
[URL].
Presentations
1. Tabei, Y., Yamanishi, Y., 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), 2016.07.10.
2. Yamanishi, Y., Tabei, Y., 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), 2015.07.13.
3. Kotera, M., Tabei, Y., Yamanishi, Y., Moriya, Y., Muto, A., Tokimatsu, T., 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), 2014.07.13.
4. Tabei, Y., Kishimoto, A., Kotera, M., Yamanishi, Y., Succinct Interval Splitting Tree for Scalable Similarity Search of Compound-Protein Pairs with Property Constraints, The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2013), 2013.08.11.
5. Kotera, M., Tabei, Y., Yamanishi, Y., Tokimatsu, T., 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), 2013.07.22.
6. Vert, J.-P., Yamanishi, Y., Supervised graph inference, The 18th Annual Conference on Neural Information Processing Systems (NIPS2004), 2004.12.14.
Membership in Academic Society
  • Japanese Society for Bioinformatics (JSBi)
  • The Chem-Bio Informatics Society (CBI)
  • The Japanese Society of Computational Statistics (JSCS)
  • International Society for Computational Biology (ISCB)
Awards
  • The ICR Award for Students (ICR: Institute for Chemical Research, Kyoto University)