English  |  正體中文  |  简体中文  |  Items with full text/Total items : 27320/39164
Visitors : 2475744      Online Users : 41
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/6022

Title: 以數學形態學為基礎之生化濾波器應用於線性抗原預測
Mathematical Morphology Based Biochemical Property Filters for Linear Epitope Prediction
Authors: Chih-Hong Liu
Contributors: NTOU:Department of Computer Science and Engineering
Keywords: 線性抗原預測;物理化學性質計算;專一性蛋白質片段;區域相對高點抗原性
Linear Epitope Prediction;Physico-chemical Scale Calculating;Unique Peptide Motif;Local Peak Antigenicity
Date: 2006
Issue Date: 2011-06-22T08:42:24Z
Abstract: 線性抗原決定位置的預測,可以提供分子與細胞生物學者在進行免疫實驗設計及抗體開發工程中,極為重要的前置分析。在過去相關的論文及研究中發現,線性抗原決定位置的物理化學特性中,不僅只位於整體抗原特性曲線的高點區段,也有部分抗原決定位置位於局部區域的相對高點區段。有鑑於此,本論文提出一套採取數學形態學的方法,進行擷取抗原特性具局部性相對高點的區段。首先,我們採用與抗原相關的物理化學性質來計算蛋白質序列的抗原分數,再將這些分數利用線性組合來表示其最後抗原分數。經由數學形態學的開放運算與原始函數的差值運算,擷取抗原特性函數中局部高點區段,並視之為可能的線性抗原決定位置候選者。除此之外,由於抗原決定位置是經由一特殊組合而被抗體所辨認的,應具有專一性的特徵,因此我們亦應用REMUS系統,從蛋白質家族序列中擷取出專一性的蛋白質片段,做為可能的線性抗原決定位置候選者。最後,本論文所提出的方法使用已發表的抗原決定位置資料庫來進行驗證,並與其他相關的線性抗原決定位置預測方法進行比較。結果顯示本論文所提出的方法,確實改善其他使用物理化學性質預測方法的缺失,並可以預測出不具整體高抗原特性的線性抗原決定位置。
Prediction of B-cell linear epitopes provides important pre-analysis for molecular and cell biologists in the tasks of immunobiological experiments and antibody design engineering. Previous studies have revealed that linear epitopes are not only occurred in the segments with global high antigenicity scales but also appeared in the relative high scale in local regions. Hence, a method adopting mathematical morphology is developed to extract segments with local peaks of antigenicity scale in this thesis. First, we adopt physico-chemical profile property data for a query protein sequence, and its antigenicity is obtained based on the linear combination of the physico-chemical scales at each residue. Subsequently, the subtraction operation between the original profile and morphologically opened profile is performed to extract local peak segments which possess relative higher antigenicity than neighboring areas and considered as possible candidates for linear epitopes. Since an epitope is recognized by an antibody in a specific combination, the epitope should possess unique characteristic in general conditions. Therefore, we employ REMUS system to confirm the specificity of unique peptide motifs from imported sequences. Finally, the proposed methodology has evaluated by released epitope databases and compared with other existing linear epitope prediction methods. The results show that our proposed methodology enhances the specificity characteristics compared to the other prediction methods, and those unpredictable epitopes based on physico-chemical properties by other methods can be resolved in this manner as well.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M95570005
Appears in Collections:

Files in This Item:

There are no files associated with this item.

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


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback