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Title: 基於蛋白質二級結構間距離矩陣之多重結構排比
Distance Matrix Analysis of Mutual Secondary Structure Pairs for Multiple Structure Alignment
Authors: Chiang-Man Sun
Contributors: NTOU:Department of Computer Science and Engineering
Keywords: 距離矩陣;區域搜尋;多重蛋白質結構排比;角度距離圖;疊代精煉演算法
distance matrix;local region search;multiple protein structure alignment;angle-distance map;iterative refinement algorithm
Date: 2009
Issue Date: 2011-07-04
Abstract: 在生物領域中,生物學家可以透過分析蛋白質序列、結構和表面來了解蛋白質與蛋白質之間的反應關係或者在演化上的關聯性。然而,蛋白質序列及結構資料庫快速成長,如何使用生物資訊演算法協助分析蛋白質之間的關係是一個急需解決且重要的課題。傳統的方法是針對蛋白質序列進行比對,但是研究發現,有部分的蛋白質序列雖相似度低,但在形成結構後卻呈現高度相似性。這樣的情況並不適合使用序列比對分析,所以本論文提出一套以蛋白質二級結構為依據的多重蛋白質排比演算法。該演算法是建構在二級結構片段在空間上的相對距離及角度所形成的矩陣特徵,以此矩陣的相似度作為蛋白質之間保留特性的依據。首先,使用最佳向量轉換技術將二級結構片段轉換成向量格式,再個別計算任兩個向量間的幾何特徵,包括距離矩陣、距離及角度等特徵,每一對二級結構向量所形成的特徵都記錄在角度距離圖上的一個特徵點。接著,透過區域篩選與矩陣比對挑選出蛋白質結構間最佳的三對候選點資訊。根據所選出的二級結構對進行向量平移與旋轉,將蛋白質結構對應到適當的初始位置,最後再使用疊代精煉演算法的技術求得最佳多重蛋白質結構的排比結果。本論文選用SCOP、Homstrad與SABmark資料庫驗證此演算法的正確性,並選取蛋白質序列相似度低的家族與其他知名系統比較。根據實驗結果證明,即使在蛋白質序列相似度低於20%的情況下,亦能達到快速正確的比對結果。
In the fields of biology, biologists comprehend the reaction and correlation of protein evolution through analyzing protein sequences, structures, and surfaces. However, the number of protein sequences and resolved structures continues to grow exponentially, so how to design bioinformatics algorithms to efficiently and effectively analyze the relationship among proteins becomes one of the most important issues. The traditional method for protein comparison applies sequence alignment, but it has been found that a certain number of protein sets hold low sequence identities but possess functional or structural similarities. Depending only on sequence alignment cannot overcome this dilemma. Hence, this study developed a multiple structure alignment system which is based on the secondary structure information. The main approach of this proposed system is to feature the characteristics of mutual correlation of secondary structure element (SSE) pairs in a protein structure. The algorithm utilizes the local matching advantages through distance matrix matching criteria to extract suitable candidates of SSE pairs from each protein. The similarity scores of compared distance matrices of mutual SSE pairs are calculated and ranked to decide representative points as key anchors for multiple structure alignment. Based on these three key anchor points, translation and rotation transformations are performed to obtain an initial alignment results and followed by an iterative refinement procedure for an optimal solution. The experimental results were verified by SCOP, Homstrad, and SABmark benchmark databases. Several cases with low sequence identity were compared with well-known protein structure alignment tools. The results showed the averagely aligned residues were evidently increased and the root-mean-square-deviance decreased within these low sequence similarity protein sets.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M96570009
Appears in Collections:[資訊工程學系] 博碩士論文

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