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 their inherent ability to model molecular structures using graph-based representations. However, maximizing the potential of such models in practice is challenging, as companies prioritize data privacy and security over collaboration initiatives to improve model performance and robustness. kMoL is an open-source machine learning library with integrated federated learning capabilities developed to address such challenges. Its key features include state-of-the-art model architectures, Bayesian optimization

SUBMITTER: Cozac R 

PROVIDER: S-EPMC11854109 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature