Correlation-based biological networks

Won Min Song*, Tomaso Aste, T. Di Matteo

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    4 Citations (Scopus)

    Abstract

    We construct a correlation-based biological network from a data set containing temporal expressions of 517 fibroblast tissue genes at transcription level. Four relevant and meaningful connected subgraphs of the network, namely: minimal spanning tree, maximal spanning tree, combined graph of minimal and maximal trees, and planar maximally filtered graph are extracted and the subgraphs' geometrical and topological properties are explored by computing relevant statistical quantities at local and global level. The results show that the subgraphs are extracting relevant information from the data set by retaining high correlation coefficients. The design principle of the underlying biological functions is reflected in the topology of the graphs.

    Original languageEnglish
    Title of host publicationComplex Systems II
    DOIs
    Publication statusPublished - 2008
    EventComplex Systems II - Canberra, Australia
    Duration: 5 Dec 20077 Dec 2007

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume6802
    ISSN (Print)0277-786X

    Conference

    ConferenceComplex Systems II
    Country/TerritoryAustralia
    CityCanberra
    Period5/12/077/12/07

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