Yoshihiro Yamanishi
Cited by
Cited by
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
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
Supervised prediction of drug–target interactions using bipartite local models
K Bleakley, Y Yamanishi
Bioinformatics 25 (18), 2397-2403, 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
Protein network inference from multiple genomic data: a supervised approach
Y Yamanishi, JP Vert, M Kanehisa
Bioinformatics 20 (suppl_1), i363-i370, 2004
Predicting drug side-effect profiles: a chemical fragment-based approach
E Pauwels, V Stoven, Y Yamanishi
BMC bioinformatics 12, 1-13, 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
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
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
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
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
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
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
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
Supervised graph inference
JP Vert, Y Yamanishi
Advances in neural information processing systems 17, 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
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
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
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
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
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