Data Mining for Systems Biology

Volume 939 of the series Methods in Molecular Biology pp 215-232


Construction of Functional Linkage Gene Networks by Data Integration

  • Bolan LinghuAffiliated withBiomarker Development Group, Translational Sciences Department, Novartis Institutes for BioMedical Research Email author 
  • , Eric A. FranzosaAffiliated withBioinformatics Program, Boston University
  • , Yu XiaAffiliated withBioinformatics Program, Boston University

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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.

Key words

Gene networks Functional association Data integration Data heterogeneity Disease gene prediction