Biological data integration using network models

Gaurav Kumar, Shoba Ranganathan

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

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.
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 (Print)9781118617113
DOIs
Publication statusPublished - 2014

Publication series

NameWiley series on bioinformatics : Computational techniques and engineering.
PublisherWiley

Fingerprint

Proteins
Data Mining
Information Storage and Retrieval
Computational Biology
Databases
Genes

Cite this

Kumar, G., & Ranganathan, S. (2014). Biological data integration using network models. In M. Elloumi, & A. Y. Zomaya (Eds.), Biological knowledge discovery handbook: preprocessing, mining and postprocessing of biological data (pp. 155-173). (Wiley series on bioinformatics : Computational techniques and engineering.). Hoboken, New Jersey: John Wiley & Sons. https://doi.org/10.1002/9781118617151.ch07
Kumar, Gaurav ; Ranganathan, Shoba. / Biological data integration using network models. Biological knowledge discovery handbook: preprocessing, mining and postprocessing of biological data. editor / Mourad Elloumi ; Albert Y Zomaya. Hoboken, New Jersey : John Wiley & Sons, 2014. pp. 155-173 (Wiley series on bioinformatics : Computational techniques and engineering.).
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Kumar, G & Ranganathan, S 2014, Biological data integration using network models. in M Elloumi & AY Zomaya (eds), Biological knowledge discovery handbook: preprocessing, mining and postprocessing of biological data. Wiley series on bioinformatics : Computational techniques and engineering., John Wiley & Sons, Hoboken, New Jersey, pp. 155-173. https://doi.org/10.1002/9781118617151.ch07

Biological data integration using network models. / Kumar, Gaurav; Ranganathan, Shoba.

Biological knowledge discovery handbook: preprocessing, mining and postprocessing of biological data. ed. / Mourad Elloumi; Albert Y Zomaya. Hoboken, New Jersey : John Wiley & Sons, 2014. p. 155-173 (Wiley series on bioinformatics : Computational techniques and engineering.).

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

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AB - 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.

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Kumar G, Ranganathan S. Biological data integration using network models. In Elloumi M, Zomaya AY, editors, Biological knowledge discovery handbook: preprocessing, mining and postprocessing of biological data. Hoboken, New Jersey: John Wiley & Sons. 2014. p. 155-173. (Wiley series on bioinformatics : Computational techniques and engineering.). https://doi.org/10.1002/9781118617151.ch07