A probabilistic approach to identify putative drug targets in biochemical networks

Journal of the Royal Society Interface

Volumn 8, Issue 59, 2011, Pages 880-895

  Murabito, Ettore ^a,b   Smallbone, Kieran ^a   Swinton, Jonathan ^c   Westerhoff, Hans V ^a,d   Steuer, Ralf ^b,e  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

^c ASTRAZENECA   (United Kingdom)

^d VU UNIVERSITY AMSTERDAM   (Netherlands)

^e HUMBOLDT UNIVERSITY   (Germany)

Author keywords

Metabolic control analysis; Monte Carlo sampling; Network based drug design

Indexed keywords

DESIGN; MONTE CARLO METHODS; PHYSIOLOGY; TOXICITY;

ACCESSIBLE INFORMATION; BIOCHEMICAL NETWORK; CLINICAL RESEARCH; COMPUTATIONAL MODEL; DRUG DESIGN; DRUG TARGETS; FLUX CONTROL; FLUX CONTROL COEFFICIENTS; HIGH EFFICACY; INDIVIDUAL COMPONENTS; KINETIC MECHANISM; KINETIC MODELS; LOW TOXICITY; METABOLIC CONTROL ANALYSIS; METABOLIC NETWORK; METABOLIC PHENOTYPE; MONTE CARLO APPROACH; MONTE CARLO SAMPLING; NETWORK-BASED; NETWORK-BASED DRUG DESIGN; NOVEL METHODS; NOVEL STRATEGIES; PHYSIOLOGICAL CONDITION; PHYSIOLOGICAL STATE; PROBABILISTIC APPROACHES; SMALL NETWORKS;

METABOLISM;

ARTICLE; BIOCHEMISTRY; DRUG DESIGN; DRUG TARGETING; KINETICS; METABOLIC REGULATION; METABOLISM; MODEL; MONTE CARLO METHOD; PHENOTYPE; PHYSIOLOGY;

EID: 79955715337     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2010.0540     Document Type: Article

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