國家衛生研究院 NHRI:Item 3990099045/4053
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/4053


    Title: A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles
    Authors: Chin, CH;Chen, SH;Ho, CW;Ko, MT;Lin, CY
    Contributors: Division of Biostatistics and Bioinformatics
    Abstract: Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful information to understand how biological systems work. Therefore, detecting functional modules is an important research topic in the post-genome era. One of functional module detecting methods is to find dense regions in Protein-Protein Interaction (PPI) networks. Most of current methods neglect confidence-scores of interactions, and pay little attention on using gene expression data to improve their results.Results: In this paper, we propose a novel hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles, and we name it HUNTER. Our method not only can extract functional modules from a weighted PPI network, but also use gene expression data as optional input to increase the quality of outcomes. Using HUNTER on yeast data, we found it can discover more novel components related with RNA polymerase complex than those existed methods from yeast interactome. And these new components show the close relationship with polymerase after functional analysis on Gene Ontology.Conclusion: A C++ implementation of our prediction method, dataset and supplementary material are available at http://hub.iis.sinica.edu.tw/Hunter/. Our proposed HUNTER method has been applied on yeast data, and the empirical results show that our method can accurately identify functional modules. Such useful application derived from our algorithm can reconstruct the biological machinery, identify undiscovered components and decipher common sub-modules inside these complexes like RNA polymerases I, II, III.
    Date: 2010-01-18
    Relation: BMC Bioinformatics. 2010 Jan 18;11(Suppl.1):Article number S25.
    Link to: http://dx.doi.org/10.1186/1471-2105-11-s1-s25
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1471-2105&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000277537900006
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=75149164017
    Appears in Collections:[Chung-Yen Lin(1999-2005)] Periodical Articles

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