Using graph theory to analyze biological networks

BioData Mining

Volumn 4, Issue 1, 2011, Pages

  Pavlopoulos, Georgios A ^a,b   Secrier, Maria ^c   Moschopoulos, Charalampos N ^d,e   Soldatos, Theodoros G ^f   Kossida, Sophia ^e   Aerts, Jan ^b   Schneider, Reinhard ^c,g   Bagos, Pantelis G ^a  

^a UNIVERSITY OF CENTRAL GREECE   (Greece)

^b UNIVERSITY OF LEUVEN   (Belgium)

^c EUROPEAN MOLECULAR BIOLOGY LABORATORY   (Germany)

^d UNIVERSITY OF PATRAS   (Greece)

^e BIOMEDICAL RESEARCH FOUNDATION   (Greece)

^f Life Biosystems GmbH   (Germany)

^g UNIVERSITY OF LUXEMBOURG   (Luxembourg)

Author keywords

biological network; clustering analysis; graph theory; node ranking

Indexed keywords

CLUSTER ANALYSIS; DATA BASE; GENE REGULATORY NETWORK; GRAPH THEORY; HUMAN; MATHEMATICAL MODEL; METABOLISM; PRIORITY JOURNAL; PROTEIN LOCALIZATION; PROTEIN PROTEIN INTERACTION; RECEIVER OPERATING CHARACTERISTIC; REVIEW; SIGNAL TRANSDUCTION; TRANSCRIPTION REGULATION;

EID: 79955130092     PISSN: None     EISSN: 17560381     Source Type: Journal    
DOI: 10.1186/1756-0381-4-10     Document Type: Review

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