Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PLoS Computational Biology

Volumn 13, Issue 2, 2017, Pages

  Filzen, Tracey M ^a   Kutchukian, Peter S ^a   Hermes, Jeffrey D ^a   Li, Jing ^a   Tudor, Matthew ^a  

^a MERCK RESEARCH LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAR CODES; CELL CULTURE; GENE EXPRESSION; STOCHASTIC SYSTEMS; THROUGHPUT;

BATCH EFFECT; BIOLOGICAL SIGNALS; CELL CULTURE MODELS; EXPRESSION PROFILE; EXPRESSION PROFILING; HIGH-THROUGHPUT; LARGE-SCALES; MRNA EXPRESSION; NOISE SOURCE; STOCHASTIC VARIATION;

DEEP LEARNING;

MITOGEN ACTIVATED PROTEIN KINASE; DRUG;

ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; GENE EXPRESSION; HIGH THROUGHPUT SCREENING; INFORMATION PROCESSING; NERVE CELL NETWORK; PERTURBATION BARCODE; PLEIOTROPY; PREDICTION; SENSITIVITY ANALYSIS; SIGNAL TRANSDUCTION; VALIDATION PROCESS; ANIMAL; CELL FUNCTION; DRUG EFFECTS; GENE EXPRESSION PROFILING; GENETICS; HIGH THROUGHPUT SEQUENCING; HUMAN; MOLECULARLY TARGETED THERAPY; PRECLINICAL STUDY; PROCEDURES;

ANIMALS; CELL PHYSIOLOGICAL PHENOMENA; DRUG EVALUATION, PRECLINICAL; GENE EXPRESSION; GENE EXPRESSION PROFILING; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MOLECULAR TARGETED THERAPY; PHARMACEUTICAL PREPARATIONS;

EID: 85014286444     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1005335     Document Type: Article

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