What can causal networks tell us about metabolic pathways?

PLoS Computational Biology

Volumn 8, Issue 4, 2012, Pages

  Blair, Rachael Hageman ^a   Kliebenstein, Daniel J ^b   Churchill, Gary A ^c  

^a UNIVERSITY AT BUFFALO   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c JACKSON LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARCHITECTURE; GRAPHIC METHODS; METABOLISM; NETWORK ARCHITECTURE; POPULATION STATISTICS; STOCHASTIC MODELS;

BIOLOGICAL PROCESS; CAUSAL NETWORK; CAUSAL RELATIONSHIPS; CORRELATION STRUCTURE; GENETIC MAPPING; GRAPHICAL MODEL; LINEAR CORRELATION; MAPPING POPULATIONS; METABOLIC PATHWAYS; NON LINEAR;

STOCHASTIC SYSTEMS;

GLUCOSINOLATE; PROTEOME;

ARABIDOPSIS; ARTICLE; BIOSYNTHESIS; CAUSAL MODELING; CAUSAL NETWORK; CONTROLLED STUDY; CORRELATION ANALYSIS; FEEDBACK SYSTEM; GENETIC EPISTASIS; GENETIC VARIABILITY; GRAPHICAL MODEL; MATHEMATICAL MODEL; METABOLIC PARAMETERS; METABOLIC PATHWAY ARCHITECTURE; METABOLIC PATHWAY RECONSTRUCTION; METABOLISM; METABOLITE; MOLECULAR DYNAMICS; MOLECULAR GENETICS; MOLECULAR PHYLOGENY; NONHUMAN; POSITION IN THE METABOLIC PATHWAY; QUANTITATIVE TRAIT LOCUS; REACTION ANALYSIS; STOCHASTIC MODEL; STOICHIOMETRY; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; COMPUTER GRAPHICS; COMPUTER SIMULATION; HUMAN; METABOLOME; PHYSIOLOGY; SIGNAL TRANSDUCTION;

ARABIDOPSIS;

ALGORITHMS; ANIMALS; COMPUTER GRAPHICS; COMPUTER SIMULATION; HUMANS; METABOLOME; MODELS, BIOLOGICAL; PROTEOME; SIGNAL TRANSDUCTION;

EID: 84861141168     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002458     Document Type: Article

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