Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation

The application of deep learning to generative molecule design has shown early promise for accelerating lead series development. However, questions remain concerning how factors like training, data set, and seed bias impact the technology's utility to medicinal and computational chemists. In th...

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Bibliographic Details

Published in:	Journal of chemical information and modeling Vol. 62; no. 4; p. 801
Main Authors:	Kang, Seung-Gu, Morrone, Joseph A, Weber, Jeffrey K, Cornell, Wendy D
Format:	Journal Article
Language:	English
Published:	United States 28.02.2022
Subjects:	Artificial Intelligence Models, Molecular Receptors, Dopamine D2 - chemistry
ISSN:	1549-960X, 1549-960X
Online Access:	Get more information
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