Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data

Molecular Pharmaceutics

Volumn 13, Issue 7, 2016, Pages 2524-2530

  Aliper, Alexander ^a   Plis, Sergey ^b,c   Artemov, Artem ^a   Ulloa, Alvaro ^c   Mamoshina, Polina ^a   Zhavoronkov, Alex ^a,d  

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

^b Datalytic Solutions   (United States)

^c MIND RESEARCH NETWORK   (United States)

^d The Biogerontology Research Foundation   (United Kingdom)

Author keywords

confusion matrix; deep learning; deep neural networks; DNN; drug discovery; drug repurposing; predictor

Indexed keywords

ANTIINFECTIVE AGENT; ANTIINFLAMMATORY AGENT; ANTILIPEMIC AGENT; ANTINEOPLASTIC AGENT; CARDIOVASCULAR AGENT; CENTRAL NERVOUS SYSTEM AGENTS; CONTRACEPTIVE AGENT; DERMATOLOGICAL AGENT; GASTROINTESTINAL AGENT; HEMATOLOGIC AGENT; RESPIRATORY TRACT AGENT; URINARY TRACT AGENT; TRANSCRIPTOME;

A549 CELL LINE; ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL LINE; CLASSIFICATION ALGORITHM; DEEP NEURAL NETWORK; DRUG CLASSIFICATION; DRUG REPOSITIONING; FEMALE; HUMAN; HUMAN CELL; INTERMETHOD COMPARISON; MCF 7 CELL LINE; MEDICAL SUBJECT HEADINGS; PC 3 CELL LINE; PREDICTION; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; TRANSCRIPTOMICS; A-549 CELL LINE; ALGORITHM; DRUG DEVELOPMENT; GENETICS; MCF-7 CELL LINE; PROCEDURES;

A549 CELLS; ALGORITHMS; DRUG DISCOVERY; DRUG REPOSITIONING; HUMANS; MCF-7 CELLS; NEURAL NETWORKS (COMPUTER); SUPPORT VECTOR MACHINE; TRANSCRIPTOME;

EID: 84979019529     PISSN: 15438384     EISSN: 15438392     Source Type: Journal    
DOI: 10.1021/acs.molpharmaceut.6b00248     Document Type: Article

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