Yoshihiro Yamanishi

83 papers A* 6A 3B 1Journal 63Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Reinforcement Learning-Driven Transformer GAN for Molecular Generation. CoRR Chen Li, Huidong Tang, Ye Zhu, Yoshihiro Yamanishi
2025	J	`jnl`	AI-driven transcriptome profile-guided hit molecule generation. Artif. Intell. Chen Li, Yoshihiro Yamanishi
2025	J	`jnl`	Establishing the Asia & Pacific Bioinformatics Joint Congress: a historic milestone in regional bioinformatics collaboration. Briefings Bioinform. Asif M. Khan, Susumu Goto, Kenta Nakai, Limsoon Wong, Diane E. Kovats, Yuki Saito, Shinya Ikematsu, Yoshihiro Yamanishi, Nurul Salwanie Che Wahid, Harpreet Singh, Pradeep Eranti, Yi-Ping Phoebe Chen, Tae-Min Kim, Shinn-Ying Ho, Jessica Cara Mar, Wataru Iwasaki, Jayaraman Valadi, Prashanth Suravajhala, Christian Schönbach, Tin Wee Tan, Shoba Ranganathan, Kiyoko F. Aoki-Kinoshita
2025	—	`conf`	Gx2Mol: De Novo Generation of Hit-Like Molecules from Gene Expression Profiles. ECML/PKDD (3) Chen Li, Yoshihiro Yamanishi
2025	A*	`conf`	InstGAN: Instant Actor-Critic-Driven GAN for De Novo Molecule Generation and Property Optimization. IJCAI Huidong Tang, Chen Li, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
2025	J	`jnl`	SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases. Bioinform. Satoko Namba, Chen Li, Noriko Yuyama Otani, Yoshihiro Yamanishi
2024	J	`jnl`	DIRECTEUR: transcriptome-based prediction of small molecules that replace transcription factors for direct cell conversion. Bioinform. Momoko Hamano, Toru Nakamura, Ryoku Ito, Yuki Shimada, Michio Iwata, Jun-ichi Takeshita, Ryohei Eguchi, Yoshihiro Yamanishi
2024	J	`jnl`	Gx2Mol: De Novo Generation of Hit-like Molecules from Gene Expression Profiles via Deep Learning. CoRR Chen Li, Yuki Matsukiyo, Yoshihiro Yamanishi
2024	A*	`conf`	GxVAEs: Two Joint VAEs Generate Hit Molecules from Gene Expression Profiles. AAAI Chen Li, Yoshihiro Yamanishi
2024	J	`jnl`	Molecular Generative Adversarial Network with Multi-Property Optimization. CoRR Huidong Tang, Chen Li, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
2024	J	`jnl`	Network-based identification of diagnosis-specific trans-omic biomarkers via integration of multiple omics data. Biosyst. Md. Mamunur Rashid, Momoko Hamano, Midori Iida, Michio Iwata, Toshiyuki Ko, Seitaro Nomura, Issei Komuro, Yoshihiro Yamanishi
2024	J	`jnl`	Quantitative evaluation of molecular generation performance of graph-based GANs. Softw. Qual. J. Jinli Zhang, Zhenbo Wang, Zongli Jiang, Man Wu, Chen Li, Yoshihiro Yamanishi
2024	J	`jnl`	Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. J. Chem. Inf. Model. Nanako Inoue, Tomokazu Shibata, Yusuke Tanaka, Hiromu Taguchi, Ryusuke Sawada, Kenshin Goto, Shogo Momokita, Morihiro Aoyagi, Takashi Hirao, Yoshihiro Yamanishi
2024	J	`jnl`	TRAITER: transformer-guided diagnosis and prognosis of heart failure using cell nuclear morphology and DNA damage marker. Bioinform. Hiromu Hayashi, Toshiyuki Ko, Zhehao Dai, Kanna Fujita, Seitaro Nomura, Hiroki Kiyoshima, Shinya Ishihara, Momoko Hamano, Issei Komuro, Yoshihiro Yamanishi
2024	A	`conf`	TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation. AISTATS Chen Li, Yoshihiro Yamanishi
2024	J	`jnl`	Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design. J. Chem. Inf. Model. Yuki Matsukiyo, Atsushi Tengeiji, Chen Li, Yoshihiro Yamanishi
2023	J	`jnl`	EarlGAN: An enhanced actor-critic reinforcement learning agent-driven GAN for de novo drug design. Pattern Recognit. Lett. Huidong Tang, Chen Li, Shuai Jiang, Huachong Yu, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
2023	—	`conf`	MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation. APWeb-WAIM (1) Huidong Tang, Chen Li, Shuai Jiang, Huachong Yu, Sayaka Kamei, Yoshihiro Yamanishi, Yasuhiko Morimoto
2023	—	`conf`	Mode Collapse Alleviation of Reinforcement Learning-based GANs in Drug Design. BIBM Zongli Jiang, Zhenbo Wang, Jinli Zhang, Man Wu, Chen Li, Yoshihiro Yamanishi
2023	—	`conf`	SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization. ECML/PKDD (1) Chen Li, Yoshihiro Yamanishi
2022	J	`jnl`	Epigenetic landscape of drug responses revealed through large-scale ChIP-seq data analyses. BMC Bioinform. Zhaonan Zou, Michio Iwata, Yoshihiro Yamanishi, Shinya Oki
2022	J	`jnl`	From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures. Bioinform. Satoko Namba, Michio Iwata, Yoshihiro Yamanishi
2022	J	`jnl`	Pathway trajectory analysis with tensor imputation reveals drug-induced single-cell transcriptomic landscape. Nat. Comput. Sci. Michio Iwata, Hiroaki Mutsumine, Yusuke Nakayama, Naomasa Suita, Yoshihiro Yamanishi
2022	J	`jnl`	Scaffold-Retained Structure Generator to Exhaustively Create Molecules in an Arbitrary Chemical Space. J. Chem. Inf. Model. Kazuma Kaitoh, Yoshihiro Yamanishi
2022	J	`jnl`	Small compound-based direct cell conversion with combinatorial optimization of pathway regulations. Bioinform. Toru Nakamura, Michio Iwata, Momoko Hamano, Ryohei Eguchi, Jun-ichi Takeshita, Yoshihiro Yamanishi
2022	J	`jnl`	TRANSDIRE: data-driven direct reprogramming by a pioneer factor-guided trans-omics approach. Bioinform. Ryohei Eguchi, Momoko Hamano, Michio Iwata, Toru Nakamura, Shinya Oki, Yoshihiro Yamanishi
2022	A*	`conf`	Transformer-based Objective-reinforced Generative Adversarial Network to Generate Desired Molecules. IJCAI Chen Li, Chikashige Yamanaka, Kazuma Kaitoh, Yoshihiro Yamanishi
2021	J	`jnl`	Lean-Docking: Exploiting Ligands' Predicted Docking Scores to Accelerate Molecular Docking. J. Chem. Inf. Model. Francois Berenger, Ashutosh Kumar, Kam Y. J. Zhang, Yoshihiro Yamanishi
2021	J	`jnl`	TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning. J. Chem. Inf. Model. Kazuma Kaitoh, Yoshihiro Yamanishi
2020	J	`jnl`	Dual graph convolutional neural network for predicting chemical networks. BMC Bioinform. Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
2020	J	`jnl`	Network-based characterization of disease-disease relationships in terms of drugs and therapeutic targets. Bioinform. Midori Iida, Michio Iwata, Yoshihiro Yamanishi
2020	J	`jnl`	Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability Domain Included. J. Chem. Inf. Model. Francois Berenger, Yoshihiro Yamanishi
2020	J	`jnl`	Space-Efficient Feature Maps for String Alignment Kernels. Data Sci. Eng. Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
2019	J	`jnl`	A Distance-Based Boolean Applicability Domain for Classification of High Throughput Screening Data. J. Chem. Inf. Model. Francois Berenger, Yoshihiro Yamanishi
2019	J	`jnl`	Chemoinformatics and structural bioinformatics in OCaml. J. Cheminformatics Francois Berenger, Kam Y. J. Zhang, Yoshihiro Yamanishi
2019	J	`jnl`	Guest Editorial for the 16th Asia Pacific Bioinformatics Conference. IEEE ACM Trans. Comput. Biol. Bioinform. Yoshihiro Yamanishi, Yasubumi Sakakibara, Yi-Ping Phoebe Chen
2019	J	`jnl`	Network-based characterization of drug-protein interaction signatures with a space-efficient approach. BMC Syst. Biol. Yasuo Tabei, Masaaki Kotera, Ryusuke Sawada, Yoshihiro Yamanishi
2019	J	`jnl`	Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm. Bioinform. Michio Iwata, Longhao Yuan, Qibin Zhao, Yasuo Tabei, Francois Berenger, Ryusuke Sawada, Sayaka Akiyoshi, Momoko Hamano, Yoshihiro Yamanishi
2019	A*	`conf`	Space-Efficient Feature Maps for String Alignment Kernels. ICDM Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
2018	J	`jnl`	Dual Convolutional Neural Network for Graph of Graphs Link Prediction. CoRR Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
2018	J	`jnl`	Scalable Alignment Kernels via Space-Efficient Feature Maps. CoRR Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh
2016	A*	`conf`	Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. KDD Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi
2016	J	`jnl`	Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. CoRR Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi
2016	J	`jnl`	Simultaneous prediction of enzyme orthologs from chemical transformation patterns for Bioinform. Yasuo Tabei, Yoshihiro Yamanishi, Masaaki Kotera
2015	J	`jnl`	Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles. J. Chem. Inf. Model. Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Masaaki Kotera, Yoshihiro Yamanishi
2015	J	`jnl`	Metabolome-scale Bioinform. Yoshihiro Yamanishi, Yasuo Tabei, Masaaki Kotera
2015	J	`jnl`	Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models. J. Chem. Inf. Model. Zheng Shao, Yuya Hirayama, Yoshihiro Yamanishi, Hiroto Saigo
2015	J	`jnl`	Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data. J. Chem. Inf. Model. Hiroaki Iwata, Ryusuke Sawada, Sayaka Mizutani, Yoshihiro Yamanishi
2015	J	`jnl`	Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data. J. Chem. Inf. Model. Ryusuke Sawada, Hiroaki Iwata, Sayaka Mizutani, Yoshihiro Yamanishi
2014	J	`jnl`	DINIES: drug-target interaction network inference engine based on supervised analysis. Nucleic Acids Res. Yoshihiro Yamanishi, Masaaki Kotera, Yuki Moriya, Ryusuke Sawada, Minoru Kanehisa, Susumu Goto
2014	J	`jnl`	Metabolome-scale prediction of intermediate compounds in multistep metabolic pathways with a recursive supervised approach. Bioinform. Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Ai Muto, Yuki Moriya, Toshiaki Tokimatsu, Susumu Goto
2013	J	`jnl`	Inferring protein domains associated with drug side effects based on drug-target interaction network. BMC Syst. Biol. Hiroaki Iwata, Sayaka Mizutani, Yasuo Tabei, Masaaki Kotera, Susumu Goto, Yoshihiro Yamanishi
2013	J	`jnl`	KCF-S: KEGG Chemical Function and Substructure for improved interpretability and prediction in chemical bioinformatics. BMC Syst. Biol. Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Yuki Moriya, Toshiaki Tokimatsu, Minoru Kanehisa, Susumu Goto
2013	J	`jnl`	KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters. Nucleic Acids Res. 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
2013	J	`jnl`	Scalable prediction of compound-protein interactions using minwise hashing. BMC Syst. Biol. Yasuo Tabei, Yoshihiro Yamanishi
2013	A*	`conf`	Succinct interval-splitting tree for scalable similarity search of compound-protein pairs with property constraints. KDD Yasuo Tabei, Akihiro Kishimoto, Masaaki Kotera, Yoshihiro Yamanishi
2013	J	`jnl`	Supervised Bioinform. Masaaki Kotera, Yasuo Tabei, Yoshihiro Yamanishi, Toshiaki Tokimatsu, Susumu Goto
2012	J	`jnl`	Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces. J. Chem. Inf. Model. Yoshihiro Yamanishi, Edouard Pauwels, Masaaki Kotera
2012	J	`jnl`	Drug target prediction using adverse event report systems: a pharmacogenomic approach. Bioinform. Masataka Takarabe, Masaaki Kotera, Yosuke Nishimura, Susumu Goto, Yoshihiro Yamanishi
2012	J	`jnl`	GENIES: gene network inference engine based on supervised analysis. Nucleic Acids Res. Masaaki Kotera, Yoshihiro Yamanishi, Yuki Moriya, Minoru Kanehisa, Susumu Goto
2012	J	`jnl`	Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinform. Yasuo Tabei, Edouard Pauwels, Véronique Stoven, Kazuhiro Takemoto, Yoshihiro Yamanishi
2012	J	`jnl`	Relating drug-protein interaction network with drug side effects. Bioinform. Sayaka Mizutani, Edouard Pauwels, Véronique Stoven, Susumu Goto, Yoshihiro Yamanishi
2011	J	`jnl`	Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions. J. Chem. Inf. Model. Yoshihiro Yamanishi, Edouard Pauwels, Hiroto Saigo, Véronique Stoven
2011	J	`jnl`	Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinform. Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi
2010	J	`jnl`	Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
2010	J	`jnl`	Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework. Bioinform. Yoshihiro Yamanishi, Masaaki Kotera, Minoru Kanehisa, Susumu Goto
2009	J	`jnl`	E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs. Bioinform. Yoshihiro Yamanishi, Masahiro Hattori, Masaaki Kotera, Susumu Goto, Minoru Kanehisa
2009	A	`conf`	Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda
2009	B	`conf`	On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
2009	J	`jnl`	Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. Bioinform. Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda
2009	J	`jnl`	Supervised prediction of drug-target interactions using bipartite local models. Bioinform. Kevin Bleakley, Yoshihiro Yamanishi
2008	J	`jnl`	KEGG for linking genomes to life and the environment. Nucleic Acids Res. Minoru Kanehisa, Michihiro Araki, Susumu Goto, Masahiro Hattori, Mika Hirakawa, Masumi Itoh, Toshiaki Katayama, Shuichi Kawashima, Shujiro Okuda, Toshiaki Tokimatsu, Yoshihiro Yamanishi
2008	A	`conf`	Prediction of drug-target interaction networks from the integration of chemical and genomic spaces. ISMB Yoshihiro Yamanishi, Michihiro Araki, Alex Gutteridge, Wataru Honda, Minoru Kanehisa
2008	—	`conf`	Supervised Bipartite Graph Inference. NIPS Yoshihiro Yamanishi
2007	J	`jnl`	Glycan classification with tree kernels. Bioinform. Yoshihiro Yamanishi, Francis R. Bach, Jean-Philippe Vert
2007	—	`conf`	Inference of Protein-Protein Interactions by Using Co-evolutionary Information. AB Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh
2006	J	`jnl`	Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions. Bioinform. Tetsuya Sato, Yoshihiro Yamanishi, Katsuhisa Horimoto, Minoru Kanehisa, Hiroyuki Toh
2005	J	`jnl`	Sensitivity analysis in functional principal component analysis. Comput. Stat. Yoshihiro Yamanishi, Yutaka Tanaka
2005	—	`conf`	Supervised enzyme network inference from the integration of genomic data and chemical information. ISMB (Supplement of Bioinformatics) Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa
2005	J	`jnl`	The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships. Bioinform. Tetsuya Sato, Yoshihiro Yamanishi, Minoru Kanehisa, Hiroyuki Toh
2004	—	`conf`	Protein network inference from multiple genomic data: a supervised approach. ISMB/ECCB (Supplement of Bioinformatics) Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru Kanehisa
2004	—	`conf`	Supervised Graph Inference. NIPS Jean-Philippe Vert, Yoshihiro Yamanishi
2003	—	`conf`	Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis. ISMB (Supplement of Bioinformatics) Yoshihiro Yamanishi, Jean-Philippe Vert, Akihiro Nakaya, Minoru Kanehisa