Forward obstacle detection system by stereo vision. - Hiroaki Iwata; Keiji Saneyoshi (ROBIO, 2012)

Forward obstacle detection in a lane by stereo vision. - Hiroaki Iwata; Keiji Saneyoshi (IECON, 2013)

Inferring protein domains associated with drug side effects based on drug-target interaction network. - Hiroaki Iwata; Sayaka Mizutani; Yasuo Tabei; Masaaki Kotera; Susumu Goto; Yoshihiro Yamanishi (BMC Syst. Biol., 2013)

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)

Machine learning accelerates MD-based binding pose prediction between ligands and proteins. - Kei Terayama; Hiroaki Iwata; Mitsugu Araki; Yasushi Okuno; Koji Tsuda (Bioinform., 2018)

Improving the Accuracy of Protein-Ligand Binding Mode Prediction Using a Molecular Dynamics-Based Pocket Generation Approach. - Mitsugu Araki; Hiroaki Iwata; Biao Ma; Atsuto Fujita; Kei Terayama; Yukari Sagae; Fumie Ono; Koji Tsuda; Narutoshi Kamiya; Yasushi Okuno (J. Comput. Chem., 2018)

kGCN: a graph-based deep learning framework for chemical structures. - Ryosuke Kojima; Shoichi Ishida; Masateru Ohta; Hiroaki Iwata; Teruki Honma; Yasushi Okuno (J. Cheminformatics, 2020)

Structure-Based de Novo Molecular Generator Combined with Artificial Intelligence and Docking Simulations. - Biao Ma; Kei Terayama; Shigeyuki Matsumoto; Yuta Isaka; Yoko Sasakura; Hiroaki Iwata; Mitsugu Araki; Yasushi Okuno (J. Chem. Inf. Model., 2021)

Predicting Total Drug Clearance and Volumes of Distribution Using the Machine Learning-Mediated Multimodal Method through the Imputation of Various Nonclinical Data. - Hiroaki Iwata; Tatsuru Matsuo; Hideaki Mamada; Takahisa Motomura; Mayumi Matsushita; Takeshi Fujiwara; Kazuya Maeda; Koichi Handa (J. Chem. Inf. Model., 2022)

Improving Compound-Protein Interaction Prediction by Self-Training with Augmenting Negative Samples. - Takuto Koyama; Shigeyuki Matsumoto; Hiroaki Iwata; Ryosuke Kojima; Yasushi Okuno (J. Chem. Inf. Model., 2023)

VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search. - Hiroaki Iwata; Taichi Nakai; Takuto Koyama; Shigeyuki Matsumoto; Ryosuke Kojima; Yasushi Okuno (J. Chem. Inf. Model., 2023)

kMoL: an open-source machine and federated learning library for drug discovery. - Romeo Cozac; Haris Hasic; Jun Jin Choong; Vincent Richard; Loic Beheshti; Cyrille Froehlich; Takuto Koyama; Shigeyuki Matsumoto; Ryosuke Kojima; Hiroaki Iwata; Aki Hasegawa; Takao Otsuka; et al. (J. Cheminformatics, 2025)