Kyushu University Academic Staff Educational and Research Activities Database
List of Papers
Yamanishi Yoshihiro Last modified date:2018.04.06

Associate Professor / Research Center for Transomics Medicine / Medical Institute of Bioregulation


Papers
1. Yamanishi, Y., Tabei, Y., Kotera, M., Statistical machine learning for agriculture and human healthcare based on biomedical big data, Agriculture as a metaphor for creativity in all human endeavors (Proceedings of Forum "Math-for-Industry" 2016), Springer, 2017.08.
2. Iwata, M., Sawada, R., Iwata, H., Kotera, M., Yamanishi, Y., Elucidating the modes of action for bioactive compounds in a cell-specific manner by large-scale chemically-induced transcriptomics, Scientific Reports, 7, 2017.01.
3. Nemoto, W., Yamanishi, Y., Limviphuvadh, V., Saito, A., Toh, H., GGIP: structure and sequence-based GPCR-GPCR interaction pair predictor, PROTEINS: Structure, Function, and Bioinformatics, 2016.06.
4. Tabei, Y., Yamanishi, Y., Kotera, M., Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction, Bioinformatics, 32, 2016.06.
5. Hizukuri, Y., Sawada, R., Yamanishi, Y., Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner, BMC Medical Genomics, 8, 10 pages, 2015.12.
6. 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.
7. Shao, Z., Hirayama, Y., Yamanishi, Y., Saigo, H., Mining discriminative patterns from graph data with multiple labels and its application to QSAR, Journal of Chemical Information and Modeling, 55, 12, 2015.12.
8. Iwata, H., Sawada, R., Mizutani, S., Kotera, M., Yamanishi, Y., Large-scale prediction of beneficial drug combinations using drug efficacy and target profiles, Journal of Chemical Information and Modeling, 55, 12, 2015.12.
9. Yamanishi, Y., Tabei, Y., Kotera, M., Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments, Bioinformatics, 31, 12, 2015.06.
10. 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.
11. Sawada, R., Kotera, M., Yamanishi, Y., Benchmarking a wide range of chemical descriptors for drug-target interaction prediction using a chemogenomic approach, Molecular Informatics, 33, 2014.12.
12. 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.
13. Kotera, M., Tabei, Y., Yamanishi, Y., Muto, A., Moriya. Y., Tokimatsu, T., Goto, S., Metabolome-scale prediction of intermediate compounds in multi-step metabolic pathways with a recursive supervised approach, Bioinformatics, 30, 2014.07.
14. Yamanishi, Y., Inferring chemogenomic features from drug-target interaction networks, Molecular Informatics, 32, 11-12, 2013.12.
15. Iwata, H., Mizutani, S., Tabei, Y., Kotera, M., Goto, S., Yamanishi, Y., Inferring protein domains associated with drug side effects based on drug-target interaction network, BMC Systems Biology, 7(Suppl 6), S18, 2013.12.
16. Tabei, Y., Yamanishi, Y., Scalable prediction of compound-protein interactions using minwise hashing, BMC Systems Biology, 7(Suppl 6), S3, 2013.12.
17. Kotera, M., Tabei, Y., Yamanishi, Y., Moriya, Y., Tokimatsu, T., Kanehisa, M., Goto, S., KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics, BMC Systems Biology, 7(Suppl 6), S2, 2013.12.
18. Tabei, Y., Kishimoto, A., Kotera, M., Yamanishi, Y., Succinct Interval Splitting Tree for Scalable Similarity Search of Compound-Protein Pairs with Property Constraints, Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2013), 2013.08.
19. Kotera, M., Tabei, Y., Yamanishi, Y., Tokimatsu, T., Goto, S., Supervised de novo reconstruction of metabolic pathways from metabolome-scale compound sets, Bioinformatics, 29, 2013.07.
20. Yamanishi, Y., Kotera, M., Takarabe, M., Goto, S., Impact of side-effect similarity on drug-target relationship: a case study using FDA adverse event report system, Genome Informatics, 2013.08.
21. Nakaya, A., Katayama, T., Itoh, M., Hiranuka, K., Kawashima, S., Moriya, Y., Okuda, S., Tanaka, M., Tokimatsu, T., Yamanishi, Y., Yoshizawa, A., Kanehisa, M., and Goto, S., KEGG OC: A large-scale automatic construction of taxonomy-based ortholog clusters, Nucleic Acids Research, 41, D353-D357, 2013.01.
22. 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.
23. Nakajima, N., Tamura, T., Yamanishi, Y., Horimoto, K. and Akutsu, T., Network completion using dynamic programming and least-squares fitting, The Scientific World Journal, 957620 (8 pages), 2012.10.
24. 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.
25. 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.
26. 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.
27. 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.
28. Pauwels, E., Stoven, V., and Yamanishi, Y., Predicting drug side-effect profiles: a chemical fragment-based approach, BMC Bioinformatics, 12, 169, 2011.05.
29. 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.
30. 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.
31. Kashima, H., Yamanishi, Y., Kato, T., Sugiyama, M., and Tsuda, K., Simultaneous Inference of Biological Networks of Multiple Species from Genome-wide Data and Evolutionary Information: A Semi-supervised Approach, Bioinformatics, 25, 2962-2968, 2009.11.
32. Bleakley, K. and Yamanishi, Y., Supervised prediction of drug-target interactions using bipartite local models, Bioinformatics, 25, 2397-2403, 2009.09.
33. 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.
34. Kashima, H., Oyama, S., Yamanishi, Y., and Tsuda, K., On Pairwise Kernels: An Efficient Alternative and Generalization Analysis, Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 5476, 1030-1037, 2009.04.
35. Kashima, H., Kato, T., Yamanishi, Y., Sugiyama, M., and Tsuda, K., Link Propagation: A Fast-semi Supervised Learning Algorithm for Link Prediction, Proceedings of the 9th SIAM Conference on Data Mining (SDM), 1099-1110, 2009.04.
36. Yamanishi, Y., Supervised Bipartite Graph Inference, Advances in Neural Information Processing Systems 21, 1841-1848, 2009.06.
37. 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.
38. Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., and Yamanishi, Y., KEGG for linking genomes to life and the environment, Nucleic Acids Res., 36, D480-D484, 2008.01.
39. Suga, A., Yamanishi, Y., Hashimoto, K., Goto, S., and Kanehisa, M., An improved scoring scheme for predicting glycan structures from gene expressison data, Genome Informatics, 18, 1, 237-246, 2007.08.
40. Sato, T., Yamanishi, Y., Horimoto, K., Kanehisa, M., and Toh, H., Inference of Protein-Protein Interactions by Using Co-evolutionary Information, Proceedings of the 2nd international conference on Algebraic Biology, 4545, 322-333, 2007.07.
41. Yamanishi, Y. and Vert, J.-P., Kernel matrix regression, Proceedings of the 12th International Conference on Applied Stochastic Models and Data Analysis (ASMDA 2007), 2007.05.
42. Yamanishi, Y., Bach, F., and Vert, J.-P., Glycan Classification with Tree Kernels, Bioinformatics, 23, 10, 1211-1216, 2007.05.
43. 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.
44. Okamoto, S., Yamanishi, Y., Ehira, S., Kawashima, S., Tonomura, K., and Kanehisa, M., Prediction of nitrogen metabolism-related genes in Anabaena by kernel-based network analysis, Proteomics, 7, 6, 900-909, 2007.03.
45. Sato, T., Yamanishi, Y., Horimoto, K., Kanehisa, M., and Toh, H., Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions, Bioinformatics, 22, 20, 2488-2492, 2006.10.
46. Yamanishi, Y. and Tanaka, Y., Sensitivity Analysis in Kernel Principal Component Analysis, Proceedings in Computational Statistics, 787-794, 2006.08.
47. Hizukuri, Y., Yamanishi, Y., Nakamura, O., Yagi, F., Goto, S., and Kanehisa, M., Extraction of leukemia specific glycan motifs by computational comparative glycomics, Carbohydrate Research, 340, 14, 2270-2278, 2005.10.
48. Sato, T., Yamanishi, Y., Kanehisa, M., and Toh, H., The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding phylogenetic relationships, Bioinformatics, 21, 17, 3482-3489, 2005.09.
49. 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.
50. Tamori, A., Yamanishi, Y., Kawashima, S., Kanehisa, M., Enomoto, M., Tanaka, H., Kubo, S., Shiomi, S., and Nishiguchi, S., Alteration of Gene Expression in Hepatitis B Virus DNA integrated human hepatocellular carcinoma, Clinical Cancer Research, 11, 16, 5821-5826, 2005.08.
51. Vert, J.-P. and Yamanishi, Y., Supervised graph inference, Advances in Neural Information Processing Systems 17, 1433-1440, 2005.06.
52. Yamanishi, Y. and Tanaka, Y., Sensitivity Analysis in Functional Principal Component Analysis, Computational Statistics, 20, 2, 313-329, 2005.06.
53. Yamanishi, Y., Vert, J.-P. and Kanehisa, M., Protein Network Inference from Multiple Genomic Data: A Supervised Approach, Bioinformatics, 20, i363-i370, 2004.08.
54. Hizukuri, Y., Yamanishi, Y., Hashimoto, K. and Kanehisa, M., Extraction of Species-specific Glycan Substructures, Genome Informatics, 15, 1, 69-81, 2004.05.
55. 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.
56. Yamanishi, Y. and Tanaka, Y., Geographically Weighted Functional Multiple Regression Analysis: A Numerical Investigation, Journal of Japanese Society of Computational Statistics, 15, 2, 307-317, 2003.06.