Yoshihiro Yamanishi

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 33

Top Topics

Convolutional Neural Network

Reinforcement Learning

Partial Least Squares Regression

Top Venues

J. Chem. Inf. Model.

Publications

Jinli Zhang, Zhenbo Wang, Zongli Jiang, Man Wu, Chen Li, Yoshihiro Yamanishi
Quantitative evaluation of molecular generation performance of graph-based GANs. Softw. Qual. J. 32 (2) (2024)
Chen Li, Yoshihiro Yamanishi
TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation. AISTATS (2024)
Chen Li, Yoshihiro Yamanishi
GxVAEs: Two Joint VAEs Generate Hit Molecules from Gene Expression Profiles. AAAI (2024)
Nanako Inoue, Tomokazu Shibata, Yusuke Tanaka, Hiromu Taguchi, Ryusuke Sawada, Kenshin Goto, Shogo Momokita, Morihiro Aoyagi, Takashi Hirao, Yoshihiro Yamanishi
Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. J. Chem. Inf. Model. 64 (14) (2024)
Yuki Matsukiyo, Chikashige Yamanaka, Yoshihiro Yamanishi
Generation of Chemical Structures of Inhibitor and Activator Candidates for Therapeutic Target Proteins by a Transformer-Based Variational Autoencoder and Bayesian Optimization. J. Chem. Inf. Model. 64 (7) (2024)
Huidong Tang, Chen Li, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
Molecular Generative Adversarial Network with Multi-Property Optimization. CoRR (2024)
Md. Mamunur Rashid, Momoko Hamano, Midori Iida, Michio Iwata, Toshiyuki Ko, Seitaro Nomura, Issei Komuro, Yoshihiro Yamanishi
Network-based identification of diagnosis-specific trans-omic biomarkers via integration of multiple omics data. Biosyst. 236 (2024)
Huidong Tang, Chen Li, Shuai Jiang, Huachong Yu, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
EarlGAN: An enhanced actor-critic reinforcement learning agent-driven GAN for de novo drug design. Pattern Recognit. Lett. 175 (2023)
Huidong Tang, Chen Li, Shuai Jiang, Huachong Yu, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation. APWeb-WAIM (1) (2023)
Zongli Jiang, Zhenbo Wang, Jinli Zhang, Man Wub, Chen Li, Yoshihiro Yamanishi
Mode Collapse Alleviation of Reinforcement Learning-based GANs in Drug Design. BIBM (2023)
Chen Li, Yoshihiro Yamanishi
SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization. ECML/PKDD (1) (2023)
Kazuma Kaitoh, Yoshihiro Yamanishi
Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space. J. Chem. Inf. Model. 62 (9) (2022)
Michio Iwata, Hiroaki Mutsumine, Yusuke Nakayama, Naomasa Suita, Yoshihiro Yamanishi
Pathway trajectory analysis with tensor imputation reveals drug-induced single-cell transcriptomic landscape. Nat. Comput. Sci. 2 (11) (2022)
Ryohei Eguchi, Momoko Hamano, Michio Iwata, Toru Nakamura, Shinya Oki, Yoshihiro Yamanishi
TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach. Bioinform. 38 (10) (2022)
Zhaonan Zou, Michio Iwata, Yoshihiro Yamanishi, Shinya Oki
Epigenetic landscape of drug responses revealed through large-scale ChIP-seq data analyses. BMC Bioinform. 23 (1) (2022)
Chen Li, Chikashige Yamanaka, Kazuma Kaitoh, Yoshihiro Yamanishi
Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules. IJCAI (2022)
Francois Berenger, Ashutosh Kumar, Kam Y. J. Zhang, Yoshihiro Yamanishi
Lean-Docking: Exploiting Ligands' Predicted Docking Scores to Accelerate Molecular Docking. J. Chem. Inf. Model. 61 (5) (2021)
Kazuma Kaitoh, Yoshihiro Yamanishi
TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning. J. Chem. Inf. Model. 61 (9) (2021)
Francois Berenger, Yoshihiro Yamanishi
Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain Included. J. Chem. Inf. Model. 60 (9) (2020)
Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
Dual graph convolutional neural network for predicting chemical networks. BMC Bioinform. (3) (2020)
Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
Space-Efficient Feature Maps for String Alignment Kernels. Data Sci. Eng. 5 (2) (2020)
Midori Iida, Michio Iwata, Yoshihiro Yamanishi
Network-based characterization of disease-disease relationships in terms of drugs and therapeutic targets. Bioinform. 36 (Supplement-1) (2020)
Yasuo Tabei, Masaaki Kotera, Ryusuke Sawada, Yoshihiro Yamanishi
Network-based characterization of drug-protein interaction signatures with a space-efficient approach. BMC Syst. Biol. (2) (2019)
Francois Berenger, Yoshihiro Yamanishi
A Distance-Based Boolean Applicability Domain for Classification of High Throughput Screening Data. J. Chem. Inf. Model. 59 (1) (2019)
Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
Space-Efficient Feature Maps for String Alignment Kernels. ICDM (2019)
Michio Iwata, Longhao Yuan, Qibin Zhao, Yasuo Tabei, Francois Berenger, Ryusuke Sawada, Sayaka Akiyoshi, Momoko Hamano, Yoshihiro Yamanishi
Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm. Bioinform. 35 (14) (2019)
Yoshihiro Yamanishi, Yasubumi Sakakibara, Yi-Ping Phoebe Chen
Guest Editorial for the 16th Asia Pacific Bioinformatics Conference. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (1) (2019)
Francois Berenger, Kam Y. J. Zhang, Yoshihiro Yamanishi
Chemoinformatics and structural bioinformatics in OCaml. J. Cheminformatics 11 (1) (2019)
Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
Scalable Alignment Kernels via Space-Efficient Feature Maps. CoRR (2018)
Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
Dual Convolutional Neural Network for Graph of Graphs Link Prediction. CoRR (2018)
Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. CoRR (2016)
Yasuo Tabei, Yoshihiro Yamanishi, Masaaki Kotera
metabolic pathway reconstruction. Bioinform. 32 (12) (2016)
Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. KDD (2016)
Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi
Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles. J. Chem. Inf. Model. 55 (12) (2015)
Yoshihiro Yamanishi, Yasuo Tabei, Masaaki Kotera
pathway reconstruction using regioisomer-sensitive graph alignments. Bioinform. 31 (12) (2015)
Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi
Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data. J. Chem. Inf. Model. 55 (2) (2015)
Zheng Shao, Yuya Hirayama, Yoshihiro Yamanishi, Hiroto Saigo
Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models. J. Chem. Inf. Model. 55 (12) (2015)
Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi
Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data. J. Chem. Inf. Model. 55 (12) (2015)
Yoshihiro Yamanishi, Masaaki Kotera, Yuki Moriya, Ryusuke Sawada, Minoru Kanehisa, Susumu Goto
DINIES: drug-target interaction network inference engine based on supervised analysis. Nucleic Acids Res. 42 (Webserver-Issue) (2014)
Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Ai Muto, Yuki Moriya, Toshiaki Tokimatsu, Susumu Goto
Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach. Bioinform. 30 (12) (2014)
Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Yuki Moriya, Toshiaki Tokimatsu, Minoru Kanehisa, Susumu Goto
KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics. BMC Syst. Biol. 7 (S-6) (2013)
Yasuo Tabei, Akihiro Kishimoto, Masaaki Kotera, Yoshihiro Yamanishi
Succinct interval-splitting tree for scalable similarity search of compound-protein pairs with property constraints. KDD (2013)
Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Toshiaki Tokimatsu, Susumu Goto
reconstruction of metabolic pathways from metabolome-scale compound sets. Bioinform. 29 (13) (2013)
Yasuo Tabei, Yoshihiro Yamanishi
Scalable prediction of compound-protein interactions using minwise hashing. BMC Syst. Biol. 7 (S-6) (2013)
Hiroaki Iwata, Sayaka Mizutani, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi
Inferring protein domains associated with drug side effects based on drug-target interaction network. BMC Syst. Biol. 7 (S-6) (2013)
Akihiro Nakaya, Toshiaki Katayama, Masumi Itoh, Kazushi Hiranuka, Shuichi Kawashima, Yuki Moriya, Shujiro Okuda, Michihiro Tanaka, Toshiaki Tokimatsu, Yoshihiro Yamanishi, Akiyasu C. Yoshizawa, Minoru Kanehisa, Susumu Goto
KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters. Nucleic Acids Res. 41 (Database-Issue) (2013)
Yasuo Tabei, Edouard Pauwels, Véronique Stoven, Kazuhiro Takemoto, Yoshihiro Yamanishi
Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinform. 28 (18) (2012)
Masataka Takarabe, Masaaki Kotera, Yosuke Nishimura, Susumu Goto, Yoshihiro Yamanishi
Drug target prediction using adverse event report systems: a pharmacogenomic approach. Bioinform. 28 (18) (2012)
Sayaka Mizutani, Edouard Pauwels, Véronique Stoven, Susumu Goto, Yoshihiro Yamanishi
Relating drug-protein interaction network with drug side effects. Bioinform. 28 (18) (2012)
Masaaki Kotera, Yoshihiro Yamanishi, Yuki Moriya, Minoru Kanehisa, Susumu Goto
GENIES: gene network inference engine based on supervised analysis. Nucleic Acids Res. 40 (Web-Server-Issue) (2012)
Yoshihiro Yamanishi, Edouard Pauwels, Masaaki Kotera
Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces. J. Chem. Inf. Model. 52 (12) (2012)
Yoshihiro Yamanishi, Edouard Pauwels, Hiroto Saigo, Véronique Stoven
Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions. J. Chem. Inf. Model. 51 (5) (2011)
Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi
Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinform. 12 (2011)
Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. (10) (2010)
Yoshihiro Yamanishi, Masaaki Kotera, Minoru Kanehisa, Susumu Goto
Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework. Bioinform. 26 (12) (2010)
Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD (2009)
Yoshihiro Yamanishi, Masahiro Hattori, Masaaki Kotera, Susumu Goto, Minoru Kanehisa
E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs. Bioinform. 25 (12) (2009)
Kevin Bleakley, Yoshihiro Yamanishi
Supervised prediction of drug-target interactions using bipartite local models. Bioinform. 25 (18) (2009)
Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda
Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. Bioinform. 25 (22) (2009)
Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM (2009)
Yoshihiro Yamanishi
Supervised Bipartite Graph Inference. NIPS (2008)
Minoru Kanehisa, Michihiro Araki, Susumu Goto, Masahiro Hattori, Mika Hirakawa, Masumi Itoh, Toshiaki Katayama, Shuichi Kawashima, Shujiro Okuda, Toshiaki Tokimatsu, Yoshihiro Yamanishi
KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36 (Database-Issue) (2008)
Yoshihiro Yamanishi, Michihiro Araki, Alex Gutteridge, Wataru Honda, Minoru Kanehisa
Prediction of drug-target interaction networks from the integration of chemical and genomic spaces. ISMB (2008)
Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh
Inference of Protein-Protein Interactions by Using Co-evolutionary Information. AB (2007)
Yoshihiro Yamanishi, Francis R. Bach, Jean-Philippe Vert
Glycan classification with tree kernels. Bioinform. 23 (10) (2007)
Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh
Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions. Bioinform. 22 (20) (2006)
Yoshihiro Yamanishi, Yutaka Tanaka
Sensitivity analysis in functional principal component analysis. Comput. Stat. 20 (2) (2005)
Tetsuya Sato, Yoshihiro Yamanishi, Minoru Kanehisa, Hiroyuki Toh
The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships. Bioinform. 21 (17) (2005)
Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa
Supervised enzyme network inference from the integration of genomic data and chemical information. ISMB (Supplement of Bioinformatics) (2005)
Jean-Philippe Vert, Yoshihiro Yamanishi
Supervised Graph Inference. NIPS (2004)
Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa
Protein network inference from multiple genomic data: a supervised approach. ISMB/ECCB (Supplement of Bioinformatics) (2004)
Yoshihiro Yamanishi, Jean-Philippe Vert, Akihiro Nakaya, Minoru Kanehisa
Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis. ISMB (Supplement of Bioinformatics) (2003)