利用蛋白質交互作用網路偵測必要性蛋白質; Essential protein detection from protein-protein interaction network

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > Electronic Thesis & Dissertation > Item 987654321/9308

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/9308

Title:	利用蛋白質交互作用網路偵測必要性蛋白質;Essential protein detection from protein-protein interaction network
Authors:	羅家宏;Chia-Hung Luo
Contributors:	資訊工程研究所
Keywords:	蛋白質交互作用;蛋白質交互作用網路;必要性蛋白質;protein interactions;essential protein;protein-protein interaction network
Date:	2006-07-14
Issue Date:	2009-09-22 11:45:07 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	了解蛋白質在細胞中所扮演的角色一直是生物學中一項很重要的課題。近年來，由於新的蛋白質交互作用偵測實驗技術相繼問世，例如yeast two-hybrid可以在一次實驗中產生出大量蛋白質交互作用的資料。有了這些大量的蛋白質交互作用資料，我們可以將這些資料轉化蛋白質交互作用網路。利用蛋白質交互作用網路來偵測必要性蛋白質。在本篇論文中，我們提出一些特性分析的方法在蛋白質交互作用網路上偵測必要性蛋白質。我們觀察蛋白質與其鄰居所形成的鄰居間最大連通子以及鄰居間最大連通子圖的密度。我們認為必要性蛋白質在蛋白質交互作用網路上的鄰居間最大連通子圖大小會比非必要性蛋白質要來得大，且鄰居間最大連通子圖之間的關係會較緊密。我們的結果顯示，這種特性分析在蛋白質交互作用網路上偵測必要性蛋白質的偵測上能夠得到比前人更好的結果。 Determining protein function in the cells is one of the most important tasks in the post-genomic era. Recently, high-throughput experiments such as yeast two-hybrid could obtain large amounts of protein-protein interaction data. We can construct the protein-protein interaction network from these protein-protein interaction data, and detect essential protein from the protein-protein interaction network. In this thesis, we first observe each protein’s maximum connected component from its neighborhood and density of the maximum component. We find that in general, an essential protein’s maximum component from its neighborhood is larger than that of a nonessential protein, and the density of maximum component from its neighborhood is denser as well. we present two approaches based on the above graph characteristics to detect essential proteins from the protein-protein interaction network. The results of our approaches are better than other earlier approaches.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

Files in This Item:

File	Size	Format

社群 sharing

Loading...