A new multiple regression approach for the construction of genetic regulatory networks

Artificial Intelligence in Medicine

Volumn 48, Issue 2-3, 2010, Pages 153-160

  Zhang, S Q ^a   Ching, W K ^b   Tsing, N K ^b   Leung, H Y ^b   Guo, D ^c  

^a FUDAN UNIVERSITY   (China)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Gene regulatory network; Multiple regression; Power law; Statistical tests

Indexed keywords

BIOLOGICAL NETWORKS; DATA SETS; GENE EXPRESSION DATA; GENE REGULATORY NETWORKS; GENETIC NETWORKS; GENETIC REGULATORY NETWORKS; HIGH-THROUGHPUT; IN-BUILDINGS; LINEAR REGRESSION MODELS; MODEL FIT; MULTIPLE REGRESSION APPROACH; MULTIPLE REGRESSION MODEL; MULTIPLE REGRESSIONS; NUMERICAL EXAMPLE; NUMERICAL RESULTS; POWER-LAW; REGULATORY RELATIONSHIPS; RESEARCH TOPICS; SAMPLING TIME; SCALE-FREE PROPERTIES; SYSTEMS BIOLOGY; TIME-SERIES GENE EXPRESSION DATA; UNDERLYING NETWORKS; YEAST CELL CYCLES;

BIOLOGY; LINEAR REGRESSION; METAL ANALYSIS; NUMERICAL ANALYSIS; STATISTICAL TESTS; YEAST;

GENE EXPRESSION;

ARTICLE; CELL CYCLE; CONTROLLED STUDY; GENE ACTIVITY; GENE EXPRESSION; GENE INTERACTION; GENE REGULATORY NETWORK; GENETIC DATABASE; LINEAR REGRESSION ANALYSIS; MATHEMATICAL COMPUTING; MULTIPLE REGRESSION; POWER OF A TEST; PREDICTION; PRIORITY JOURNAL; STATISTICAL MODEL; SYSTEMS BIOLOGY; TIME SERIES ANALYSIS; YEAST CELL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL CYCLE; DATA MINING; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, FUNGAL; GENE REGULATORY NETWORKS; LINEAR MODELS; MODELS, GENETIC; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SYSTEMS BIOLOGY; SYSTEMS INTEGRATION; TIME FACTORS;

EID: 77951623857     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2009.11.001     Document Type: Article

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