English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90452/105769 (86%)
Visitors : 11962866      Online Users : 516
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://asiair.asia.edu.tw/ir/handle/310904400/87031


    Title: In silico Identification of Potential Targets and Drugs for Non Small Cell Lung Cancer
    Authors: 黃建宏;Chien-Hung Huang;吳泯祐;Min-You Wu;張牧新;Peter Mu-Hsin Chang;黃奇英;Chi-Ying Huang;吳家樂;Ng, Ka-Lok
    Contributors: 生物與醫學資訊學系
    Date: 2014-03
    Issue Date: 2014-11-13 15:00:33 (UTC+8)
    Abstract: Lung cancer is one of the leading causes of death in both the USA and Taiwan, and it is thought that the cause of cancer could be because of the gain of function of an oncoprotein or the loss of function of a tumour suppressor protein. Consequently, these proteins are potential targets for drugs. In this study, differentially expressed genes are identified, via an expression dataset generated from lung adenocarcinoma tumour and adjacent non-tumour tissues. This study has integrated many complementary resources, that is, microarray, protein-protein interaction and protein complex. After constructing the lung cancer protein-protein interaction network (PPIN), the authors performed graph theory analysis of PPIN. Highly dense modules are identified, which are potential cancer-associated protein complexes. Up- and down-regulated communities were used as queries to perform functional enrichment analysis. Enriched biological processes and pathways are determined. These sets of up- and down-regulated genes were submitted to the Connectivity Map web resource to identify potential drugs. The authors' findings suggested that eight drugs from DrugBank and three drugs from NCBI can potentially reverse certain up- and down-regulated genes' expression. In conclusion, this study provides a systematic strategy to discover potential drugs and target genes for lung cancer.
    Relation: IET Systems Biology;8(2):56-66.
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

    Files in This Item:

    There are no files associated with this item.



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


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