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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Veröffentlicht in:	Molecular pharmaceutics Jg. 14; H. 9; S. 3098
Hauptverfasser:	Kadurin, Artur, Nikolenko, Sergey, Khrabrov, Kuzma, Aliper, Alex, Zhavoronkov, Alex
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 05.09.2017
Schlagworte:	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-Zugang:	Weitere Angaben
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