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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Vydané v:	Journal of chemical information and modeling Ročník 62; číslo 4; s. 801
Hlavní autori:	Kang, Seung-Gu, Morrone, Joseph A, Weber, Jeffrey K, Cornell, Wendy D
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 28.02.2022
Predmet:	Artificial Intelligence Models, Molecular Receptors, Dopamine D2 - chemistry
ISSN:	1549-960X, 1549-960X
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