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Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics.
Moore, Jason H; Boczko, Erik M; Summar, Marshall L.
Afiliación
  • Moore JH; Computational Genetics Laboratory, Department of Genetics, Norris Cotton Cancer Center, Dartmouth Medical School, Lebanon, NH 03756, USA. jason.h.moore@dartmouth.edu
Mol Genet Metab ; 84(2): 104-11, 2005 Feb.
Article en En | MEDLINE | ID: mdl-15670716
Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two or more DNA sequence variations. We review here this approach and then discuss how it can be used to model biochemical and metabolic data in the context of genetic studies of human disease susceptibility.
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Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Predisposición Genética a la Enfermedad / Genética Médica / Modelos Biológicos Límite: Humans Idioma: En Revista: Mol Genet Metab Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA / METABOLISMO Año: 2005 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
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Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Predisposición Genética a la Enfermedad / Genética Médica / Modelos Biológicos Límite: Humans Idioma: En Revista: Mol Genet Metab Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA / METABOLISMO Año: 2005 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos