druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico

Deep generative adversarial networks (GANs) are the emerging technology in drug discovery and biomarker development. In our recent work, we demonstrated a proof-of-concept of implementing deep generative adversarial autoencoder (AAE) to identify new molecular fingerprints with predefined anticancer...

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Bibliographic Details

Published in:	Molecular pharmaceutics Vol. 14; no. 9; p. 3098
Main Authors:	Kadurin, Artur, Nikolenko, Sergey, Khrabrov, Kuzma, Aliper, Alex, Zhavoronkov, Alex
Format:	Journal Article
Language:	English
Published:	United States 05.09.2017
Subjects:	Artificial Intelligence Computer Simulation Concept Formation Learning Models, Theoretical Neural Networks (Computer) generative adversarial network deep learning adversarial autoencoder drug discovery variational autoencoder
ISSN:	1543-8392, 1543-8392
Online Access:	Get more information
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