Significance analysis of time-series transcriptomic data: A methodology that enables the identification and further exploration of the differentially expressed genes at each time-point

Biotechnology and Bioengineering

Volumn 98, Issue 3, 2007, Pages 668-678

  Dutta, Bhaskar ^a   Snyder, Robert ^a   Klapa, Maria I ^a,b  

^a UNIVERSITY OF MARYLAND   (United States)

^b INSTITUTE OF CHEMICAL ENGINEERING SCIENCES   (Greece)

Author keywords

Bioinformatics; Dynamic omic profiling; Highthroughput analysis; Hypothesis testing; Systems biology; Time point comparison

Indexed keywords

ALGORITHMS; BIOINFORMATICS; BIOLOGICAL SYSTEMS; DATA ACQUISITION; INFORMATION ANALYSIS; MICROARRAYS; TIME SERIES ANALYSIS;

DYNAMIC-OMIC PROFILING; HIGHTHROUGHPUT ANALYSIS; HYPOTHESIS TESTING; SYSTEMS BIOLOGY; TIME-POINT COMPARISON;

GENE EXPRESSION;

ALGORITHM; ARTICLE; COMPUTER PROGRAM; CORRELATION ANALYSIS; FINGER DERMATOGLYPHICS; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; GENE SEQUENCE; GENETIC ANALYSIS; GENETIC TRANSCRIPTION; GENETIC VARIABILITY; METHODOLOGY; MICROARRAY ANALYSIS; TRANSCRIPTOMICS;

ALGORITHMS; ARABIDOPSIS; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, PLANT; MODELS, BIOLOGICAL; PROTEOME; SIGNAL TRANSDUCTION; TIME FACTORS; TRANSCRIPTION FACTORS; TRANSCRIPTION, GENETIC;

EID: 35048896054     PISSN: 00063592     EISSN: 10970290     Source Type: Journal    
DOI: 10.1002/bit.21432     Document Type: Article

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