tailieunhanh - Báo cáo y học: " Identification of functional modules that correlate with phenotypic difference: the influence of network topology"

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: Identification of functional modules that correlate with phenotypic difference: the influence of network topology. | Hung et al. Genome Biology 2010 11 R23 http 2010 11 2 R23 Genome Biology METHOD Open Access Identification of functional modules that correlate with phenotypic difference the influence of network topology Jui-Hung Hung 1 Troy W Whitfield2 Tun-Hsiang Yang1 Zhenjun Hu1 3 Zhiping Weng1 2 3 Charles DeLisi1 3 Abstract One of the important challenges to post-genomic biology is relating observed phenotypic alterations to the underlying collective alterations in genes. Current inferential methods however invariably omit large bodies of information on the relationships between genes. We present a method that takes account of such information - expressed in terms of the topology of a correlation network - and we apply the method in the context of current procedures for gene set enrichment analysis. Background A central problem in cell biology is to infer functional molecular modules underlying cellular alterations from high throughput data such as differential gene protein or metabolite concentrations. A number of computational techniques have been developed that use expression for class distinction to identify from among a priori defined sets of functionally or structurally related genes those that correlate with phenotypic difference see for example Goeman and Buhlmann 1 . More sophisticated approaches have used random forests to capture nonlinear and complex information in expression profiles 2 applied linear transformations to measure the discriminative information of genes 3 and combined information from multiple assessments 4 . One of the most widely used methods gene set enrichment analysis GSEA 5 ranks genes according to their differential expression and then uses a modified Kolmogorov-Smirnov statistic weighted K-S test as a basis for determining whether genes from a prespecified set for example Kyoto Encyclopaedia of Genes and Genomes KEGG pathways or Gene Ontology GO terms are overrepresented toward the top or bottom of the list correcting for .