Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

Proceedings of the National Academy of Sciences of the United States of America

Volumn 103, Issue 50, 2006, Pages 19033-19038

  Lezon, Timothy R ^a   Banavar, Jayanth R ^a   Cieplak, Marek ^c   Maritan, Amos ^d   Fedoroff, Nina V ^a,b,e  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b SANTA FE INSTITUTE   (United States)

^c INSTITUTE OF PHYSICS   (Poland)

^d UNIVERSITY OF PADOVA   (Italy)

^e PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Gene interactions; Metabolic oscillations; Network inference; Signaling

Indexed keywords

ANALYTIC METHOD; ARTICLE; CELL ACTIVITY; CELL COMMUNICATION; CELL DIVISION; CELL METABOLISM; ENTROPY; GENE EXPRESSION; GENE INTERACTION; MICROARRAY ANALYSIS; NONHUMAN; OSCILLATION; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE; SIGNAL TRANSDUCTION; BIOLOGY; COMPUTER SIMULATION; DNA MICROARRAY; GENETICS;

SACCHAROMYCES CEREVISIAE;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; ENTROPY; GENE EXPRESSION; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SACCHAROMYCES CEREVISIAE;

EID: 35548985891     PISSN: 00278424     EISSN: None     Source Type: Journal    
DOI: 10.1073/pnas.0609152103     Document Type: Article

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