An ensemble learning approach to reverse-engineering transcriptional regulatory networks from time-series gene expression data

BMC Genomics

Volumn 10, Issue SUPPL. 1, 2009, Pages

  Ruan, Jianhua ^a   Deng, Youping ^b,c   Perkins, Edward J ^d   Zhang, Weixiong ^e,f  

^a One UTSA Circle   (United States)

^b SpecPro Inc   (United States)

^c University of Southern Mississippi   (United States)

^d U S ARMY ENGINEER RESEARCH AND DEVELOPMENT CENTER   (United States)

^e WASHINGTON UNIVERSITY IN ST LOUIS   (United States)

^f WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR;

ACCURACY; CELL BUDDING; CELL CYCLE; CELL CYCLE PHASE; CHROMATIN IMMUNOPRECIPITATION; CONFERENCE PAPER; CONTROLLED STUDY; DECISION TREE; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; MACHINE LEARNING; MICROARRAY ANALYSIS; NONHUMAN; PROMOTER REGION; PROTEIN BINDING; RELIABILITY; SACCHAROMYCES CEREVISIAE; TIME SERIES ANALYSIS; TRANSCRIPTION REGULATION; VALIDATION PROCESS; ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; CYTOLOGY; DNA MICROARRAY; GENE EXPRESSION; GENETICS; METABOLISM; METHODOLOGY;

SACCHAROMYCETALES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL CYCLE; CHROMATIN IMMUNOPRECIPITATION; COMPUTATIONAL BIOLOGY; GENE EXPRESSION; GENE REGULATORY NETWORKS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROMOTER REGIONS, GENETIC; SACCHAROMYCES CEREVISIAE; TRANSCRIPTION FACTORS;

EID: 67650514305     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-10-S1-S8     Document Type: Conference Paper

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