English  |  正體中文  |  简体中文  |  Items with full text/Total items : 12145/12927 (94%)
Visitors : 905076      Online Users : 838
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/3990099045/2273


    Title: POINT: a database for the prediction of protein-protein interactions based on the orthologous interactome
    Authors: Huang, TW;Tien, AC;Lee, YCG;Huang, WS;Lee, YCG;Peng, CL;Tseng, HH;Kao, CY;Huang, CYF
    Contributors: Division of Molecular and Genomic Medicine
    Abstract: One possible path towards understanding the biological function of a target protein is through the discovery of how it interfaces within protein-protein interaction networks. The goal of this study was to create a virtual protein-protein interaction model using the concepts of orthologous conservation (or interologs) to elucidate the interacting networks of a particular target protein. POINT (the (p) under bar rediction (o) under barf (int) under bar eractome database) is a functional database for the prediction of the human protein-protein interactome based on available orthologous interactome datasets. POINT integrates several publicly accessible databases, with emphasis placed on the extraction of a large quantity of mouse, fruit fly, worm and yeast protein-protein interactions datasets from the Database of Interacting Proteins (DIP), followed by conversion of them into a predicted human interactome. In addition, protein-protein interactions require both temporal synchronicity and precise spatial proximity. POINT therefore also incorporates correlated mRNA expression clusters obtained from cell cycle microarray databases and subcellular localization from Gene Ontology to further pinpoint the likelihood of biological relevance of each predicted interacting sets of protein partners.
    Keywords: Biochemical Research Methods;Biotechnology & Applied Microbiology;Computer Science, Interdisciplinary Applications;Mathematical & Computational Biology;Statistics & Probability
    Date: 2004-11-22
    Relation: Bioinformatics. 2004 Nov;20(17):3273-3276.
    Link to: http://dx.doi.org/10.1093/bioinformatics/bth366
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1367-4803&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000225361400048
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=10244242604
    Appears in Collections:[黃奇英(1998-2005)] 期刊論文

    Files in This Item:

    File Description SizeFormat
    000225361400048.pdf74KbAdobe PDF1272View/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