English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 905150      Online Users : 894
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/6935


    Title: Spotlight: Assembly of protein complexes by integrating graph clustering methods
    Authors: Chin, CH;Chen, SH;Chen, CY;Hsiung, CA;Ho, CW;Ko, MT;Lin, CY
    Contributors: Division of Biostatistics and Bioinformatics
    Abstract: As is generally assumed, clusters in protein–protein interaction (PPI) networks perform specific, crucial functions in biological systems. Various network community detection methods have been developed to exploit PPI networks in order to identify protein complexes and functional modules. Due to the potential role of various regulatory modes in biological networks, a single method may just apply a single graph property and neglects communities highlighted by other network properties. This work presents a novel integration method to capture protein modules/ protein complexes by multiple network features detected by different algorithms. The integration method is further implemented in a web-based platform with a highly effective interactive network analyser. Conventionally adopted methods with different perspectives on network community detection (e.g., CPM, FastGreedy, HUNTER, MCL, LE, SpinGlass, and WalkTrap) are also executed simultaneously. Analytical results indicate that the proposed method performs better than the conventional ones. The proposed approach can capture the transcription and RNA splicing machineries from the yeast protein network. Meanwhile, proteins that are highly associated with each other, yet not described in both machineries are also identified. In sum, a protein that is closely connected to components of a known module or a complex in the network view implies the functional association among them. Importantly, our method can detect these unique network features, thus facilitating efforts to discover unknown components of functional modules/ protein complexes.
    Date: 2013-04
    Relation: Gene. 2013 Apr;158(1):42-51.
    Link to: http://dx.doi.org/10.1016/j.gene.2012.11.087
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0378-1119&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000316424100007
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84875379772
    Appears in Collections:[林仲彥(1999-2005)] 期刊論文
    [熊昭] 期刊論文

    Files in This Item:

    File Description SizeFormat
    SDO0378111912015673.pdf1773KbAdobe PDF611View/Open


    All items in NHRI are protected by copyright, with all rights reserved.

    Related Items in TAIR

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback