PubMed ID
20187943
UMMS Affiliation
Department of Biochemistry and Molecular Pharmacology; Program in Bioinformatics and Integrative Biology
Date
3-2-2010
Document Type
Article
Subjects
Adenoma; Colorectal Neoplasms; Computational Biology; Databases, Genetic; Gene Expression Regulation, Neoplastic; *Gene Regulatory Networks; Genotype; Humans; Lung Neoplasms; Phenotype; Small Cell Lung Carcinoma
Disciplines
Bioinformatics | Genomics | Life Sciences | Medicine and Health Sciences
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.
Rights and Permissions
Citation: Genome Biol. 2010;11(2):R23. Epub 2010 Feb 26. Link to article on publisher's site