Molecular generative model based on conditional variational autoencoder for de novo molecular design-Reference-Cited by-同舟云学术

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Molecular generative model based on conditional variational autoencoder for de novo molecular design

Published:2018-07-11 Issue:1 Volume:10 Page:
ISSN:1758-2946
Container-title:Journal of Cheminformatics
language:en
Short-container-title:J Cheminform

Author:

Lim Jaechang,Ryu Seongok,Kim Jin Woo,Kim Woo Youn^ORCID

Funder

National Research Foundation of Korea

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1186/s13321-018-0286-7.pdf

Reference30 articles.

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2. Polishchuk PG, Madzhidov TI, Varnek A (2013) Estimation of the size of drug-like chemical space based on GDB-17 data. J Comput Aided Mol Des 27(8):675

3. Shoichet BK (2004) Virtual screening of chemical libraries. Nature 432(7019):862. https://doi.org/10.1038/nature03197

4. Scior T, Bender A, Tresadern G, Medina-Franco JL, Martínez-Mayorga K, Langer T, Cuanalo-Contreras K, Agrafiotis DK (2012) Recognizing pitfalls in virtual screening: a critical review. J Chem Inf Model 52(4):867. https://doi.org/10.1021/ci200528d

5. Cheng T, Li Q, Zhou Z, Wang Y, Bryant SH (2012) Structure-based virtual screening for drug discovery: a problem-centric review. AAPS J 14(1):133. https://doi.org/10.1208/s12248-012-9322-0

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