Biological data integration using network models

Gaurav Kumar, Shoba Ranganathan

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    2 Citations (Scopus)

    Abstract

    Enormous amounts of biological data have been generated and stored in various public and private databases. In this chapter, the authors explore the utility of various data sources as resources to facilitate the integration-driven knowledge synthesis using a network-based model system. Their aim is to demonstrate the utility of network models to understand protein function, genetic interaction, and their importance in gene association to various human disease conditions. Here, they review the major computational methodologies available for predicting protein and gene interactions. To understand the molecular mechanisms of human disease conditions, we require a data-mining approach aimed at modeling the functional relationships between genes and/or proteins as complex independent networks. Besides data integration, another critical challenge in computational biology is to develop methods and tools for analyzing, interpreting, and visualizing genomic data to underline the functioning of biological systems.
    Original languageEnglish
    Title of host publicationBiological knowledge discovery handbook
    Subtitle of host publicationpreprocessing, mining and postprocessing of biological data
    EditorsMourad Elloumi, Albert Y Zomaya
    Place of PublicationHoboken, New Jersey
    PublisherJohn Wiley & Sons
    Pages155-173
    Number of pages19
    ISBN (Electronic)9781118617151
    ISBN (Print)9781118617113, 9781118853726
    DOIs
    Publication statusPublished - 2014

    Publication series

    NameWiley series on bioinformatics : Computational techniques and engineering.
    PublisherWiley

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