Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research

Author:

David Laurianne,Arús-Pous Josep,Karlsson Johan,Engkvist Ola,Bjerrum Esben Jannik,Kogej Thierry,Kriegl Jan M.,Beck Bernd,Chen Hongming

Funder

H2020 Marie Skłodowska-Curie Actions

Publisher

Frontiers Media SA

Subject

Pharmacology (medical),Pharmacology

Reference186 articles.

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3. Randomized SMILES strings improve the quality of molecular generative models Arús-PousJ. JohanssonS. PtykhodkoO. BjerrumE. J. TyrchanC. ReymondJ.-L. 10.26434/chemrxiv.8639942.v2ChemRxiv Prepr.2019

4. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays;Baell;J. Med. Chem.,2010

5. Seven year itch: pan-assay interference compounds (PAINS) in 2017 - utility and limitations;Baell;ACS Chem. Biol.,2018

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