title: Construction of functional linkage gene networks by data integration.
abstract: Networks of functional associations between genes have recently been successfully used for gene function and disease-related research. A typical approach for constructing such functional linkage gene networks (FLNs) is based on the integration of diverse high-throughput functional genomics datasets. Data integration is a nontrivial task due to the heterogeneous nature of the different data sources and their variable accuracy and completeness. The presence of correlations between data sources also adds another layer of complexity to the integration process. In this chapter we discuss an approach for constructing a human FLN from data integration and a subsequent application of the FLN to novel disease gene discovery. Similar approaches can be applied to nonhuman species and other discovery tasks.
authors.affiliation: Translational Sciences Department, Novartis Institutes for BioMedical Research, Cambridge, MA, USA. bolan.linghu@novartis.com
authors.forename: Bolan
authors.initials: B
authors.lastname: Linghu
authors.forename: Eric A
authors.initials: EA
authors.lastname: Franzosa
authors.forename: Yu
authors.initials: Y
authors.lastname: Xia
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D008040:Genetic Linkage; D023281:Genomics / Q000379:methods; D006801:Humans; D008958:Models, Molecular