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Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Derivation of genetic interaction networks from quantitative phenotype data. | Method Open Access Derivation of genetic interaction networks from quantitative phenotype data Becky L Drees Vesteinn Thorsson Gregory W Carter Alexander W Rives Marisa Z Raymond Iliana Avila-Campillo Paul Shannon and Timothy Galitski Address Institute for Systems Biology 1441 N. 34th Street Seattle WA 98103 USA. H These authors contributed equally to this work. Correspondence Timothy Galitski. E-mail tgalitski@systemsbiology.org Published 31 March 2005 Genome Biology 2005 6 R38 doi 10.1 186 gb-2005-6-4-r38 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2005 6 4 R38 Received 3 December 2004 Revised 4 February 2005 Accepted 1 March 2005 2005 Drees et al. licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract We have generalized the derivation of genetic-interaction networks from quantitative phenotype data. Familiar and unfamiliar modes of genetic interaction were identified and defined. A network was derived from agar-invasion phenotypes of mutant yeast. Mutations showed specific modes of genetic interaction with specific biological processes. Mutations formed cliques of significant mutual information in their large-scale patterns of genetic interaction. These local and global interaction patterns reflect the effects of gene perturbations on biological processes and pathways. Background Phenotypes are determined by complex interactions among gene variants and environmental factors. In biomedicine these interacting elements take various forms inherited and somatic human gene variants and polymorphisms epigenetic effects on gene activity environmental agents and drug therapies including drug combinations. The success of predictive preventive and personalized .
