Harnessing Big Data for Systems Pharmacology

Annual Review of Pharmacology and Toxicology

Volumn 57, Issue , 2017, Pages 245-262

  Xie, Lei ^a,b   Draizen, Eli J ^c,d   Bourne, Philip E ^c,e  

^a City College of the City University of New York   (United States)

^b CITY UNIVERSITY OF NEW YORK   (United States)

^c NATIONAL INSTITUTES OF HEALTH   (United States)

^d BOSTON UNIVERSITY   (United States)

^e NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

cloud computing; computational modeling; data science; machine learning; NIH Commons; semantic web; systems biology; systems pharmacology modeling

Indexed keywords

ALGORITHM; BIOPHYSICS; CLOUD COMPUTING; DRUG MECHANISM; GENETIC ASSOCIATION STUDY; GENOMICS; HUMAN; MACHINE LEARNING; MATHEMATICAL MODEL; NONHUMAN; PHARMACOLOGY; PHENOTYPE; PRIORITY JOURNAL; RELIABILITY; REPRODUCIBILITY; REVIEW; SOFTWARE; STANDARDIZATION; STATISTICS; SYSTEMS BIOLOGY; TREATMENT RESPONSE; VALIDITY; ANIMAL; CLINICAL PHARMACOLOGY; FACTUAL DATABASE; HIGH THROUGHPUT SCREENING; PROCEDURES; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA; TRENDS;

ANIMALS; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; PHARMACOLOGY, CLINICAL; SYSTEMS BIOLOGY;

EID: 85009135184     PISSN: 03621642     EISSN: 15454304     Source Type: Book Series    
DOI: 10.1146/annurev-pharmtox-010716-104659     Document Type: Review

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