English  |  正體中文  |  简体中文  |  Items with full text/Total items : 93288/109022 (86%)
Visitors : 20989257      Online Users : 718
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/310904400/2550

    Title: Prediction of Cancerous Genes using cDNA Microarray Data and Gene Regulation Relationship
    Authors: K.C. Shih
    Contributors: Department of Bioinformatics
    Date: 2005
    Issue Date: 2009-11-06 22:31:46 (UTC+8)
    Publisher: Asia University
    Abstract: Several of ten thousands functional genes control the growth, genetics, and behavior of living organisms by regulating different gene expressions. The genes in a normal cell control the process of cell growth, differentiation, reproduction, and apoptosis via multiple steps of interactive regulation mechanism. The mechanism of gene regulation is a very important process in human beings. If there is something wrong in the gene regulation mechanism, it may cause some diseases.

    It is very difficult to identify the regulatory relations among genes in human genome. Traditional biological research methods consume huge amont of time and man strength. In recent years, with the rapid development of technologies, cDNA can be used to analyze the changes of gene expressions in different cells in a high throughput manner. In this paper, we propose a novel bioinformatics approach to predict the regulatory network of genes based on differential expressions of cDNA microarray databases for tumor and normal tissues. The differences in regulatory networks of genes for tumor and normal tissues reveal the information of finding possible cancer-related genes. The predicted cancerous genes can then be provided to biologists for further verification through biological experiments.

    In this thesis, we propose a bioinformatic approach to discover possible cancer-related genes based on Synchronous Truth Table of cDNA microarray databases for cancer and normal tissues.
    Appears in Collections:[生物資訊與醫學工程學系 ] 博碩士論文

    Files in This Item:

    File SizeFormat

    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