Masahito Ohue

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 32

Top Topics

Molecular Dynamics

Graph Representation

Top Venues

J. Chem. Inf. Model.

Publications

Kairi Furui, Masahito Ohue
Fastlomap: faster lead optimization mapper algorithm for large-scale relative free energy perturbation. J. Supercomput. 80 (10) (2024)
Takafumi Ueki, Masahito Ohue
Antibody complementarity-determining region design using AlphaFold2 and DDG predictor. J. Supercomput. 80 (9) (2024)
Taisuke Boku, Masatake Sugita, Ryohei Kobayashi, Shinnosuke Furuya, Takuya Fujie, Masahito Ohue, Yutaka Akiyama
Improving Performance on Replica-Exchange Molecular Dynamics Simulations by Optimizing GPU Core Utilization. ICPP (2024)
Masahito Ohue, Kotoyu Sasayama, Masami Takata
Mathematical modeling and problem solving: from fundamentals to applications. J. Supercomput. 80 (10) (2024)
Jianan Li, Keisuke Yanagisawa, Masatake Sugita, Takuya Fujie, Masahito Ohue, Yutaka Akiyama
CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides. J. Chem. Inf. Model. 63 (7) (2023)
Apakorn Kengkanna, Masahito Ohue
Enhancing Model Learning and Interpretation Using Multiple Molecular Graph Representations for Compound Property and Activity Prediction. CoRR (2023)
Apakorn Kengkanna, Masahito Ohue
Enhancing Model Learning and Interpretation using Multiple Molecular Graph Representations for Compound Property and Activity Prediction. CIBCB (2023)
Kairi Furui, Masahito Ohue
Faster Lead Optimization Mapper Algorithm for Large-Scale Relative Free Energy Perturbation. CoRR (2023)
Jianan Li, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama
Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning. Bioinform. 38 (4) (2022)
Masatake Sugita, Takuya Fujie, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama
Lipid Composition Is Critical for Accurate Membrane Permeability Prediction of Cyclic Peptides by Molecular Dynamics Simulations. J. Chem. Inf. Model. 62 (18) (2022)
Kairi Furui, Masahito Ohue
Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain. CoRR (2022)
Kairi Furui, Masahito Ohue
Compound Virtual Screening by Learning-to-Rank with Gradient Boosting Decision Tree and Enrichment-based Cumulative Gain. CIBCB (2022)
Masatake Sugita, Satoshi Sugiyama, Takuya Fujie, Yasushi Yoshikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama
Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations. J. Chem. Inf. Model. 61 (7) (2021)
Masahito Ohue, Yutaka Akiyama
MEGADOCK-GUI: a GUI-based complete cross-docking tool for exploring protein-protein interactions. CoRR (2021)
Takatsugi Kosugi, Masahito Ohue
Quantitative Estimate of Protein-Protein Interaction Targeting Drug-likeness. CIBCB (2021)
Shunya Sugita, Masahito Ohue
Drug-target affinity prediction using applicability domain based on data density. CIBCB (2021)
Masahito Ohue, Kento Aoyama, Yutaka Akiyama
High-performance cloud computing for exhaustive protein-protein docking. CoRR (2020)
Kento Aoyama, Masanori Kakuta, Yuri Matsuzaki, Takashi Ishida, Masahito Ohue, Yutaka Akiyama
Development of Computational Pipeline Software for Genome/Exome Analysis on the K Computer. Supercomput. Front. Innov. 7 (1) (2020)
Kento Aoyama, Hiroki Watanabe, Masahito Ohue, Yutaka Akiyama
Multiple HPC Environments-Aware Container Image Configuration Workflow for Large-Scale All-to-All Protein-Protein Docking Calculations. SCFA (2020)
Masahito Ohue, Ryota Ii, Keisuke Yanagisawa, Yutaka Akiyama
Molecular activity prediction using graph convolutional deep neural network considering distance on a molecular graph. CoRR (2019)
Masahito Ohue, Marina Yamasawa, Kazuki Izawa, Yutaka Akiyama
Parallelized Pipeline for Whole Genome Shotgun Metagenomics with GHOSTZ-GPU and MEGAN. BIBE (2019)
Keren Jiang, Di Zhang, Tsubasa Iino, Risa Kimura, Tatsuo Nakajima, Kana Shimizu, Masahito Ohue, Yutaka Akiyama
A playful tool for predicting protein-protein docking. MUM (2019)
Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama
MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions. BMC Bioinform. (4) (2018)
Tomohiro Ban, Masahito Ohue, Yutaka Akiyama
Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem. Comput. Biol. Chem. 73 (2018)
Keisuke Yanagisawa, Shunta Komine, Rikuto Kubota, Masahito Ohue, Yutaka Akiyama
Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm. Comput. Biol. Chem. 74 (2018)
Takashi Tajimi, Naoki Wakui, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama
Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques. BMC Bioinform. (19) (2018)
Shogo D. Suzuki, Masahito Ohue, Yutaka Akiyama
PKRank: a novel learning-to-rank method for ligand-based virtual screening using pairwise kernel and RankSVM. Artif. Life Robotics 23 (2) (2018)
Masahito Ohue, Takuro Yamazaki, Tomohiro Ban, Yutaka Akiyama
Link Mining for Kernel-Based Compound-Protein Interaction Predictions Using a Chemogenomics Approach. ICIC (2) (2017)
Keisuke Yanagisawa, Shunta Komine, Shogo D. Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama
Spresso: an ultrafast compound pre-screening method based on compound decomposition. Bioinform. 33 (23) (2017)
Masahito Ohue, Takuro Yamazaki, Tomohiro Ban, Yutaka Akiyama
Link Mining for Kernel-based Compound-Protein Interaction Predictions Using a Chemogenomics Approach. CoRR (2017)
Tomohiro Ban, Masahito Ohue, Yutaka Akiyama
Efficient hyperparameter optimization by using Bayesian optimization for drug-target interaction prediction. ICCABS (2017)
Takehiro Shimoda, Shuji Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama
Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures. BMC Syst. Biol. 9 (S-1) (2015)
Masahito Ohue, Takehiro Shimoda, Shuji Suzuki, Yuri Matsuzaki, Takashi Ishida, Yutaka Akiyama
MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers. Bioinform. 30 (22) (2014)
Takehiro Shimoda, Takashi Ishida, Shuji Suzuki, Masahito Ohue, Yutaka Akiyama
MEGADOCK-GPU: Acceleration of Protein-Protein Docking Calculation on GPUs. BCB (2013)
Yuri Matsuzaki, Nobuyuki Uchikoga, Masahito Ohue, Takehiro Shimoda, Toshiyuki Sato, Takashi Ishida, Yutaka Akiyama
MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments. Source Code Biol. Medicine 8 (2013)
Takehiro Shimoda, Masahito Ohue, Yuri Matsuzaki, Takayuki Fujiwara, Nobuyuki Uchikoga, Takashi Ishida, Yutaka Akiyama
The MEGADOCK project: Ultra-high-speed protein-protein interaction prediction tools on supercomputing environments. BCB (2013)
Masahito Ohue, Yuri Matsuzaki, Takehiro Shimoda, Takashi Ishida, Yutaka Akiyama
Improvement of Protein-Protein Interaction Prediction by Integrating Template-Based and Template-Free Protein Docking. BCB (2013)
Masahito Ohue, Yuri Matsuzaki, Takashi Ishida, Yutaka Akiyama
Improvement of the Protein-Protein Docking Prediction by Introducing a Simple Hydrophobic Interaction Model: An Application to Interaction Pathway Analysis. PRIB (2012)