DINIES: drug-target interaction network inference engine based on supervised analysis. - Yoshihiro Yamanishi; Masaaki Kotera; Yuki Moriya; Ryusuke Sawada; Minoru Kanehisa; Susumu Goto (Nucleic Acids Res., 2014)

Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles. - Hiroaki Iwata; Ryusuke Sawada; Sayaka Mizutani; Masaaki Kotera; Yoshihiro Yamanishi (J. Chem. Inf. Model., 2015)

Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data. - Hiroaki Iwata; Ryusuke Sawada; Sayaka Mizutani; Yoshihiro Yamanishi (J. Chem. Inf. Model., 2015)

Target-Based Drug Repositioning Using Large-Scale Chemical-Protein Interactome Data. - Ryusuke Sawada; Hiroaki Iwata; Sayaka Mizutani; Yoshihiro Yamanishi (J. Chem. Inf. Model., 2015)

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm. - Michio Iwata; Longhao Yuan; Qibin Zhao; Yasuo Tabei; Francois Berenger; Ryusuke Sawada; Sayaka Akiyoshi; Momoko Hamano; Yoshihiro Yamanishi (Bioinform., 2019)

Network-based characterization of drug-protein interaction signatures with a space-efficient approach. - Yasuo Tabei; Masaaki Kotera; Ryusuke Sawada; Yoshihiro Yamanishi (BMC Syst. Biol., 2019)

Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. - Nanako Inoue; Tomokazu Shibata; Yusuke Tanaka; Hiromu Taguchi; Ryusuke Sawada; Kenshin Goto; Shogo Momokita; Morihiro Aoyagi; Takashi Hirao; Yoshihiro Yamanishi (J. Chem. Inf. Model., 2024)