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Journal of Chemical Information and Modeling
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July 17, 2023
Improving Compound-Protein Interaction Prediction by Self-Training with Augmenting Negative Samples
Takuto Koyama, Shigeyuki Matsumoto, Hiroaki Iwata, et al.
Journal of Chemical Information and Modeling
|
November 22, 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, et al.
International Journal of Pharmaceutics
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February 9, 2024
Feature extraction of particle morphologies of pharmaceutical excipients from scanning electron microscope images using convolutional neural networks
Hiroaki Iwata, Yoshihiro Hayashi, Takuto Koyama, et al.
Journal of Cheminformatics
|
January 31, 2026
Chemical genomics language model toward reliable and explainable compound-protein interaction exploration
Takuto Koyama, Hayato Tsumura, Ryunosuke Okita, et al.
Journal of Cheminformatics
|
February 26, 2025
kMoL: an open-source machine and federated learning library for drug discovery
Romeo Cozac, Haris Hasic, Jun Jin Choong, et al.
Journal of Chemical Information and Modeling
|
October 22, 2025
Improving ADME Prediction with Multitask Graph Neural Networks and Assessing Explainability in Lead Optimization
Shoma Ito, Takuto Koyama, Shigeyuki Matsumoto, et al.
Journal of Cheminformatics
|
January 10, 2026
Empowering federated learning for robust compound-protein interaction prediction across heterogeneous cross-pharma domains
Takuto Koyama, Hiroaki Iwata, Ryosuke Kojima, et al.
Cell Death & Disease
|
November 11, 2024
Synergistic involvement of the NZF domains of the LUBAC accessory subunits HOIL-1L and SHARPIN in the regulation of LUBAC function
Yusuke Toda, Hiroaki Fujita, Koshiki Mino, et al.
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Search research articles
Search
Showing results (1-10 of 8) with videos related to
Sort By:
Page
of 1
Journal of Chemical Information and Modeling
|
July 17, 2023
Improving Compound-Protein Interaction Prediction by Self-Training with Augmenting Negative Samples
Takuto Koyama, Shigeyuki Matsumoto, Hiroaki Iwata, et al.
Journal of Chemical Information and Modeling
|
November 22, 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, et al.
International Journal of Pharmaceutics
|
February 9, 2024
Feature extraction of particle morphologies of pharmaceutical excipients from scanning electron microscope images using convolutional neural networks
Hiroaki Iwata, Yoshihiro Hayashi, Takuto Koyama, et al.
Journal of Cheminformatics
|
January 31, 2026
Chemical genomics language model toward reliable and explainable compound-protein interaction exploration
Takuto Koyama, Hayato Tsumura, Ryunosuke Okita, et al.
Journal of Cheminformatics
|
February 26, 2025
kMoL: an open-source machine and federated learning library for drug discovery
Romeo Cozac, Haris Hasic, Jun Jin Choong, et al.
Journal of Chemical Information and Modeling
|
October 22, 2025
Improving ADME Prediction with Multitask Graph Neural Networks and Assessing Explainability in Lead Optimization
Shoma Ito, Takuto Koyama, Shigeyuki Matsumoto, et al.
Journal of Cheminformatics
|
January 10, 2026
Empowering federated learning for robust compound-protein interaction prediction across heterogeneous cross-pharma domains
Takuto Koyama, Hiroaki Iwata, Ryosuke Kojima, et al.
Cell Death & Disease
|
November 11, 2024
Synergistic involvement of the NZF domains of the LUBAC accessory subunits HOIL-1L and SHARPIN in the regulation of LUBAC function
Yusuke Toda, Hiroaki Fujita, Koshiki Mino, et al.
Page
of 1