| KEGG for linking genomes to life and the environment M Kanehisa, M Araki, S Goto, M Hattori, M Hirakawa, M Itoh, T Katayama, ... Nucleic acids research 36 (suppl_1), D480-D484, 2007 | 6588 | 2007 |
| Prediction of drug–target interaction networks from the integration of chemical and genomic spaces Y Yamanishi, M Araki, A Gutteridge, W Honda, M Kanehisa Bioinformatics 24 (13), i232-i240, 2008 | 1166 | 2008 |
| Supervised prediction of drug–target interactions using bipartite local models K Bleakley, Y Yamanishi Bioinformatics 25 (18), 2397-2403, 2009 | 671 | 2009 |
| Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework Y Yamanishi, M Kotera, M Kanehisa, S Goto Bioinformatics 26 (12), i246-i254, 2010 | 518 | 2010 |
| Protein network inference from multiple genomic data: a supervised approach Y Yamanishi, JP Vert, M Kanehisa Bioinformatics 20 (suppl_1), i363-i370, 2004 | 312 | 2004 |
| Predicting drug side-effect profiles: a chemical fragment-based approach E Pauwels, V Stoven, Y Yamanishi BMC bioinformatics 12, 1-13, 2011 | 262 | 2011 |
| Relating drug–protein interaction network with drug side effects S Mizutani, E Pauwels, V Stoven, S Goto, Y Yamanishi Bioinformatics 28 (18), i522-i528, 2012 | 229 | 2012 |
| Link propagation: A fast semi-supervised learning algorithm for link prediction H Kashima, T Kato, Y Yamanishi, M Sugiyama, K Tsuda Proceedings of the 2009 SIAM international conference on data mining, 1100-1111, 2009 | 187 | 2009 |
| The inference of protein–protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships T Sato, Y Yamanishi, M Kanehisa, H Toh Bioinformatics 21 (17), 3482-3489, 2005 | 173 | 2005 |
| Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis Y Yamanishi, JP Vert, A Nakaya, M Kanehisa Bioinformatics 19 (suppl_1), i323-i330, 2003 | 167 | 2003 |
| Drug side-effect prediction based on the integration of chemical and biological spaces Y Yamanishi, E Pauwels, M Kotera Journal of chemical information and modeling 52 (12), 3284-3292, 2012 | 156 | 2012 |
| Drug target prediction using adverse event report systems: a pharmacogenomic approach M Takarabe, M Kotera, Y Nishimura, S Goto, Y Yamanishi Bioinformatics 28 (18), i611-i618, 2012 | 156 | 2012 |
| KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters A Nakaya, T Katayama, M Itoh, K Hiranuka, S Kawashima, Y Moriya, ... Nucleic acids research 41 (D1), D353-D357, 2012 | 129 | 2012 |
| Supervised enzyme network inference from the integration of genomic data and chemical information Y Yamanishi, JP Vert, M Kanehisa Bioinformatics 21 (suppl_1), i468-i477, 2005 | 128 | 2005 |
| Supervised graph inference JP Vert, Y Yamanishi Advances in neural information processing systems 17, 2004 | 123 | 2004 |
| DINIES: drug–target interaction network inference engine based on supervised analysis Y Yamanishi, M Kotera, Y Moriya, R Sawada, M Kanehisa, S Goto Nucleic acids research 42 (W1), W39-W45, 2014 | 120 | 2014 |
| Identification of chemogenomic features from drug–target interaction networks using interpretable classifiers Y Tabei, E Pauwels, V Stoven, K Takemoto, Y Yamanishi Bioinformatics 28 (18), i487-i494, 2012 | 104 | 2012 |
| E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs Y Yamanishi, M Hattori, M Kotera, S Goto, M Kanehisa Bioinformatics 25 (12), i179-i186, 2009 | 96 | 2009 |
| Extracting sets of chemical substructures and protein domains governing drug-target interactions Y Yamanishi, E Pauwels, H Saigo, V Stoven Journal of chemical information and modeling 51 (5), 1183-1194, 2011 | 92 | 2011 |
| Alteration of gene expression in human hepatocellular carcinoma with integrated hepatitis B virus DNA A Tamori, Y Yamanishi, S Kawashima, M Kanehisa, M Enomoto, ... Clinical cancer research 11 (16), 5821-5826, 2005 | 90 | 2005 |
