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Functional Gene Networks and Their Applications

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Networks in Systems Biology

Part of the book series: Computational Biology ((COBO,volume 32))

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Abstract

One essential goal in functional genomics is to understand the functions and functional interactions of genes. The functional interaction between genes can happen in many ways and at different molecular levels, including co-expression, protein–protein interaction, shared sequence motif, etc. The functional interaction supported by such heterogeneous genomic data can be integrated into functional gene networks (FGNs) based on machine learning approaches. In FGNs, a node represents a gene and the edge indicates the probability that two genes co-function in the same pathway or biological process. By addressing the functional difference between isoforms generated from the same gene, recent efforts have focused on building FGNs at the finer isoform level, i.e., functional isoform networks (FINs). In this chapter, we will first present an introduction to FGNs and describe how heterogeneous genomic data can be integrated to build the network by machine learning approaches. We will then describe the refinement of FGNs from global networks to tissue-specific networks and from gene level to isoform level. Finally, we will describe and discuss the applications of FGNs in predicting gene functions and disease genes.

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Author information

Authors and Affiliations

  1. Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410083, Hunan, People’s Republic of China

    Hong-Dong Li

  2. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA

    Yuanfang Guan

Authors
  1. Hong-Dong Li
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  2. Yuanfang Guan
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Correspondence to Hong-Dong Li .

Editor information

Editors and Affiliations

  1. Scientific Computing Program (PROCC), Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Fabricio Alves Barbosa da Silva

  2. CDTS, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

    Nicolas Carels

  3. Department of Computational Modeling, National Laboratory of Scientific Computing, Petrópolis, Rio de Janeiro, Brazil

    Marcelo Trindade dos Santos

  4. Graduate Program in Nanobiosystems, Federal University of Rio de Janeiro, Duque de Caxias, Rio de Janeiro, Brazil

    Francisco José Pereira Lopes

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Li, HD., Guan, Y. (2020). Functional Gene Networks and Their Applications. In: da Silva, F.A.B., Carels, N., Trindade dos Santos, M., Lopes, F.J.P. (eds) Networks in Systems Biology. Computational Biology, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-030-51862-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-51862-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51861-5

  • Online ISBN: 978-3-030-51862-2

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