Yoshihiro Yamanishi

Summary

Affiliation: Ecole des Mines de Paris
Country: France

Publications

  1. doi Chemogenomic approaches to infer drug-target interaction networks
    Yoshihiro Yamanishi
    Institut Curie, Centre de recherche Biologie du developpement, U900 Unit of Bioinformatics and Computational Systems Biology of Cancer, Paris, France
    Methods Mol Biol 939:97-113. 2013
  2. pmc Prediction of drug-target interaction networks from the integration of chemical and genomic spaces
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 24:i232-40. 2008
  3. pmc Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework
    Yoshihiro Yamanishi
    Mines ParisTech, Centre for Computational Biology, 35 rue Saint Honore, F 77305 Fontainebleau Cedex, Institut Curie, F 75248, INSERM U900, F 75248, Paris, France
    Bioinformatics 26:i246-54. 2010
  4. ncbi Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions
    Tetsuya Sato
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 22:2488-92. 2006
  5. ncbi Supervised enzyme network inference from the integration of genomic data and chemical information
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:i468-77. 2005
  6. doi Extracting sets of chemical substructures and protein domains governing drug-target interactions
    Yoshihiro Yamanishi
    Mines ParisTech, Centre for Computational Biology, 35 rue Saint Honore, F 77305 Fontainebleau Cedex, France, Institut Curie, F 75248, Paris, France, and INSERM U900, F 75248 Paris, France
    J Chem Inf Model 51:1183-94. 2011
  7. ncbi Integer programming-based method for completing signaling pathways and its application to analysis of colorectal cancer
    Takeyuki Tamura
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 24:193-203. 2010
  8. pmc GENIES: gene network inference engine based on supervised analysis
    Masaaki Kotera
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 40:W162-7. 2012
  9. pmc KEGG for linking genomes to life and the environment
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Nucleic Acids Res 36:D480-4. 2008
  10. pmc E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Bioinformatics 25:i179-86. 2009

Detail Information

Publications25

  1. doi Chemogenomic approaches to infer drug-target interaction networks
    Yoshihiro Yamanishi
    Institut Curie, Centre de recherche Biologie du developpement, U900 Unit of Bioinformatics and Computational Systems Biology of Cancer, Paris, France
    Methods Mol Biol 939:97-113. 2013
    ..We also discuss the characteristics of each method, and show some perspectives toward future research direction...
  2. pmc Prediction of drug-target interaction networks from the integration of chemical and genomic spaces
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 24:i232-40. 2008
    ..Therefore, there is a strong incentive to develop new methods capable of detecting these potential drug-target interactions efficiently...
  3. pmc Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework
    Yoshihiro Yamanishi
    Mines ParisTech, Centre for Computational Biology, 35 rue Saint Honore, F 77305 Fontainebleau Cedex, Institut Curie, F 75248, INSERM U900, F 75248, Paris, France
    Bioinformatics 26:i246-54. 2010
    ..There is therefore a strong incentive to develop new methods capable of detecting these potential drug-target interactions efficiently...
  4. ncbi Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions
    Tetsuya Sato
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 22:2488-92. 2006
    ..In this study, we introduced a partial correlation coefficient as a new measure for the degree of co-evolution between proteins, and proposed its use to predict protein-protein interactions...
  5. ncbi Supervised enzyme network inference from the integration of genomic data and chemical information
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:i468-77. 2005
    ..There is, therefore, an incentive to develop methods to reconstruct the unknown parts of the metabolic network and to identify genes coding for missing enzymes...
  6. doi Extracting sets of chemical substructures and protein domains governing drug-target interactions
    Yoshihiro Yamanishi
    Mines ParisTech, Centre for Computational Biology, 35 rue Saint Honore, F 77305 Fontainebleau Cedex, France, Institut Curie, F 75248, Paris, France, and INSERM U900, F 75248 Paris, France
    J Chem Inf Model 51:1183-94. 2011
    ..The proposed method constitutes a contribution to the recent field of chemogenomics that aims to connect the chemical space with the biological space. ..
  7. ncbi Integer programming-based method for completing signaling pathways and its application to analysis of colorectal cancer
    Takeyuki Tamura
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 24:193-203. 2010
    ..In this paper, we develop an integer programming-based method for inferring such changes by using gene expression data. We test our method on its ability to reconstruct the pathway of colorectal cancer in the KEGG database...
  8. pmc GENIES: gene network inference engine based on supervised analysis
    Masaaki Kotera
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 40:W162-7. 2012
    ..GENIES (http://www.genome.jp/tools/genies/) is publicly available as one of the genome analysis tools in GenomeNet...
  9. pmc KEGG for linking genomes to life and the environment
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Nucleic Acids Res 36:D480-4. 2008
    ..KEGG DRUG contains all approved drugs in the US and Japan, and KEGG DISEASE is a new database linking disease genes, pathways, drugs and diagnostic markers...
  10. pmc E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Bioinformatics 25:i179-86. 2009
    ..There are numerous reactions known to be present in various pathways but without any official EC numbers, most of which have no hope to be given ones because of the lack of the published articles on enzyme assays...
  11. ncbi Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach
    Masaaki Kotera
    Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology, 2 12 1 Ookayama, Meguro ku, Tokyo, 152 8550, Japan, PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332 0012, Japan, Division of System Cohort, Medical Institute of Bioregulation, Kyushu University, 3 1 1 Maidashi, Higashi ku, Fukuoka 812 8582, Japan, Institute for Advanced Study, Kyushu University, 6 10 1 Hakozaki, Higashi ku, Fukuoka 812 8581, Japan, Graduate School of Biological Sciences, Nara Institute of Science and Technology NAIST, 8916 5 Takayama, Ikoma, Nara 630 0192, Japan and Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 30:i165-i174. 2014
    ..Therefore, an important challenge in metabolomics is the de novo reconstruction of potential reaction networks on a metabolome-scale...
  12. pmc Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets
    Masaaki Kotera
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 29:i135-44. 2013
    ..Therefore, the most important challenge in metabolomics is the automated de novo reconstruction of metabolic pathways, which includes the elucidation of previously unknown reactions to bridge the metabolic gaps...
  13. ncbi Glycan classification with tree kernels
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 23:1211-6. 2007
    ..Recently, comprehensive data about the structure and function of glycans have been accumulated, therefore the need for methods and algorithms to analyze these data is growing fast...
  14. ncbi An improved scoring scheme for predicting glycan structures from gene expression data
    Akitsugu Suga
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 18:237-46. 2007
    ....
  15. pmc Network completion using dynamic programming and least-squares fitting
    Natsu Nakajima
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    ScientificWorldJournal 2012:957620. 2012
    ..We also perform computational experiments using both artificially generated and real gene expression time series data...
  16. pmc Drug target prediction using adverse event report systems: a pharmacogenomic approach
    Masataka Takarabe
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 28:i611-i618. 2012
    ..The identification of all potential drug targets has become an important issue in drug repositioning to reuse known drugs for new therapeutic indications...
  17. pmc Relating drug-protein interaction network with drug side effects
    Sayaka Mizutani
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611 0011, Japan
    Bioinformatics 28:i522-i528. 2012
    ....
  18. ncbi Extraction of leukemia specific glycan motifs in humans by computational glycomics
    Yoshiyuki Hizukuri
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Carbohydr Res 340:2270-8. 2005
    ....
  19. ncbi The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships
    Tetsuya Sato
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:3482-9. 2005
    ..The incentive of our study was to solve this problem by improving the method of extracting the co-evolutionary information regarding the protein pairs...
  20. pmc Supervised prediction of drug-target interactions using bipartite local models
    Kevin Bleakley
    Mines ParisTech, Centre for Computational Biology, Fontainebleau, France
    Bioinformatics 25:2397-403. 2009
    ..This, however, remains extremely challenging due to, amongst other things, the rarity of known drug-target interactions...
  21. ncbi Prediction of missing enzyme genes in a bacterial metabolic network. Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan
    FEBS J 274:2262-73. 2007
    ..We observed that the predicted gene products catalyzed the expected reactions; no activity was seen when both gene products were omitted from the reaction...
  22. pmc Predicting drug side-effect profiles: a chemical fragment-based approach
    Edouard Pauwels
    Mines ParisTech, Centre for Computational Biology, 35 rue Saint Honore, F 77305 Fontainebleau Cedex, France
    BMC Bioinformatics 12:169. 2011
    ....
  23. ncbi Extraction of species-specific glycan substructures
    Yoshiyuki Hizukuri
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 15:69-81. 2004
    ..We confirmed that the characteristic substructures extracted by our method correspond to the substructures which are known as the species-specific sugar chain of gamma-glutamyltranspeptidases in the kidney...
  24. ncbi Prediction of nitrogen metabolism-related genes in Anabaena by kernel-based network analysis
    Shinobu Okamoto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Japan
    Proteomics 7:900-9. 2007
    ..The prediction of functional relationships between proteins rather than functions of individual proteins will thus assist the discovery from the large-scale datasets...
  25. ncbi Extraction of organism groups from phylogenetic profiles using independent component analysis
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 13:61-70. 2002
    ..The 9 extracted components out of 18 predefined components well represented the organism groups as categorized in KEGG. Furthermore, we performed the cluster analysis and obtained the hierarchy of organism groups...