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A Graph Community Approach for Constructing microRNA Networks

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Big Data Computing and Communications (BigCom 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9196))

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Abstract

Network integration methods are critical in understanding the underlying mechanisms of genetic perturbations and susceptibility to disease. Often, expression quantitative trait loci (eQTL) mapping is used to integrate two layers of genomic data. However, eQTL associations only represent the direct associations among eQTLs and affected genes. To understand the downstream effects of eQTLs on gene expression, we propose a network community approach to construct eQTL networks that integrates multiple data sources. By using this approach, we can view the genetic networks consisting of genes affected directly or indirectly by genetic variants. To extend the eQTL network, we use a protein-protein interaction network as a base network and a spin glass community detection algorithm to find hubs of genes that are indirectly affected by eQTLs. This method contributes a novel approach to identifying indirect targets that may be affected by variant perturbations. To demonstrate its application, we apply this approach to study how microRNAs affect the expression of target genes and their indirect downstream targets in ovarian cancer.

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Author information

Authors and Affiliations

  1. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, USA

    Benika Hall, Andrew Quitadamo & Xinghua Shi

Authors
  1. Benika Hall
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  2. Andrew Quitadamo
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  3. Xinghua Shi
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Corresponding author

Correspondence to Xinghua Shi .

Editor information

Editors and Affiliations

  1. University of North Carolina at Charlotte, Charlotte, North Carolina, USA

    Yu Wang

  2. Rutgers Business School, Newark, New Jersey, USA

    Hui Xiong

  3. Illinois Institute of Technology, Chicago, Illinois, USA

    Shlomo Argamon

  4. Illinois Institute of Technology, Chicago, Illinois, USA

    XiangYang Li

  5. Harbin Institute of Technology, Harbin, China

    JianZhong Li

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© 2015 Springer International Publishing Switzerland

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Hall, B., Quitadamo, A., Shi, X. (2015). A Graph Community Approach for Constructing microRNA Networks. In: Wang, Y., Xiong, H., Argamon, S., Li, X., Li, J. (eds) Big Data Computing and Communications. BigCom 2015. Lecture Notes in Computer Science(), vol 9196. Springer, Cham. https://doi.org/10.1007/978-3-319-22047-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-22047-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22046-8

  • Online ISBN: 978-3-319-22047-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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