Abstract
Diverse sets of compounds were classified according to biological activity by use of a partitioning approach based on principal component analysis in conjunction with a genetic algorithm for molecular descriptor evaluation. Combinations of 236 molecular property and structural key descriptors were explored for their performance in classifying 317 molecules belonging to 21 distinct biological activity classes from various sources. Preferred descriptor combinations were further explored by complete factorial analysis. In these calculations, compounds having similar specific activity were predicted with greater than 80% accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of chemical information and computer sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
