kMoL: an open-source machine and federated learning library for drug discovery

kMoL: an open-source machine and federated learning library for drug discovery

Abstract Machine learning is quickly becoming integral to drug discovery pipelines, particularly quantitative structure-activity relationship (QSAR) and absorption, distribution, metabolism, and excretion (ADME) tasks. Graph Convolutional Network (GCN) models have proven especially promising due to...

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Bibliographic Details
Main Authors: 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, Yasushi Okuno
Format: Article
Language:English
Published: BMC 2025-02-01
Series:Journal of Cheminformatics
Subjects:
Machine learning
Federated learning
Drug discovery
Deep learning
Graph convolutional networks
Distributed learning
Online Access:https://doi.org/10.1186/s13321-025-00967-9
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