ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation
ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation is a scholarly work, published in 2024 in ''Journal of Chemical Information and Modeling''. The main subjects of the publication include drug design, artificial intelligence, generative grammar, small molecule, computer science, microfluidics, domain, materials informatics industry, machine learning, Python, computational biology, chemical space, and drug discovery. The authors present a computationally efficient active learning methodology and demonstrate its applicability to targeted molecular generation.