The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology

Oncotarget

Volumn 8, Issue 7, 2017, Pages 10883-10890

  Kadurin, Artur ^a,b,c,d   Aliper, Alexander ^b   Kazennov, Andrey ^b,g   Mamoshina, Polina ^b,e   Vanhaelen, Quentin ^b   Khrabrov, Kuzma ^a   Zhavoronkov, Alex ^b,f,g  

^a Building 2   (Russian Federation)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c KAZAN FEDERAL UNIVERSITY   (Russian Federation)

^d STEKLOV MATHEMATICAL INSTITUTE   (Russian Federation)

^e UNIVERSITY OF OXFORD   (United Kingdom)

^f The Biogerontology Research Foundation   (United Kingdom)

^g MOSCOW INSTITUTE OF PHYSICS AND TECHNOLOGY   (Russian Federation)

Author keywords

Adversarial autoencoder; Artificial intelligence; Deep learning; Drug discovery; Generative adversarian networks

Indexed keywords

ADVERSARIAL AUTOENCODER; ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL ASSAY; CONTROLLED STUDY; DEEP NEURAL NETWORK; GROWTH INHIBITION; HUMAN; HUMAN CELL; INFORMATION PROCESSING; MCF-7 CELL LINE; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; MOLECULAR FINGERPRINT; MOLECULAR GENETICS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; DRUG SCREENING; DRUG THERAPY; HIGH THROUGHPUT SCREENING; K-562 CELL LINE; MACHINE LEARNING; PROCEDURES; REPRODUCIBILITY; TUMOR CELL LINE;

ANTINEOPLASTIC AGENT;

ANTINEOPLASTIC AGENTS; CELL LINE, TUMOR; DRUG SCREENING ASSAYS, ANTITUMOR; DRUG THERAPY; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; K562 CELLS; MACHINE LEARNING; MCF-7 CELLS; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS;

EID: 85012890514     PISSN: None     EISSN: 19492553     Source Type: Journal    
DOI: 10.18632/oncotarget.14073     Document Type: Article

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