Monte Carlo sampling and principal component analysis of flux distributions yield topological and modular information on metabolic networks

Journal of Theoretical Biology

Volumn 242, Issue 2, 2006, Pages 389-400

  Sariyar, Berna ^a   Perk, Sinem ^b   Akman, Uǧur ^c   Hortaçsu, Amable ^c  

^a MARMARA UNIVERSITY   (Turkey)

^b Illinois Institute of Technology   (United States)

^c BOGAZICI UNIVERSITY   (Turkey)

Author keywords

Flux balance analysis; Linear programming; Modular information; Monte Carlo sampling; Principal component analysis

Indexed keywords

AMMONIA; GLUCOSE;

FECAL COLIFORM; GROWTH; MONTE CARLO ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; STEADY-STATE EQUILIBRIUM; SURVIVAL; TOPOLOGY;

AEROBIC METABOLISM; ARTICLE; CHEMICAL REACTION; CORRELATION ANALYSIS; ESCHERICHIA COLI; METABOLISM; MONTE CARLO METHOD; NONHUMAN; PHENOTYPE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; STATISTICAL SIGNIFICANCE; STEADY STATE;

AMMONIA; ANIMALS; COMPUTATIONAL BIOLOGY; CULTURE MEDIA; ESCHERICHIA COLI; GLUCOSE; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; MONTE CARLO METHOD; PRINCIPAL COMPONENT ANALYSIS;

ESCHERICHIA COLI;

EID: 33747192003     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2006.03.007     Document Type: Article

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