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博碩士論文 etd-0902110-103900 詳細資訊
Title page for etd-0902110-103900
論文名稱
Title
蛋白質結構預測結果之效益評估函數
A New Fitness Function for Evaluating the Quality of Predicted Protein Structures
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
49
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2010-07-07
繳交日期
Date of Submission
2010-09-02
關鍵字
Keywords
蛋白質、三級結構、預測
prediction, tertiary structure, protein
統計
Statistics
本論文已被瀏覽 5693 次,被下載 950
The thesis/dissertation has been browsed 5693 times, has been downloaded 950 times.
中文摘要
蛋白質結構在我們了解此蛋白質的功能上扮演著非常重要的角色。而從蛋白質的一級序列預測其三級結構在生物資訊領域中也有著重要的幫助。蛋白質的真實結構可經由一些極耗費時間及成本的技術取得,但蛋白質結構預測可幫助我們預先判斷此蛋白質的功能。在這裡我們發展出三項數值可以運用在蛋白質骨幹結構預測上的效益評估函數。從結果中可以顯示,我們經由GP(Genetic Programming)產生出來的效益評估函數於CASP8競賽中的蛋白質預測序列中有80%高於平均值。
Abstract
For understanding the function of a protein, the protein structure plays an important role. The prediction of protein structure from its primary sequence has significant assistance in bioinformatics. Generally, the real protein structures can be reconstructed by some costly techniques, but predicting the protein structures helps us guess the functional expression of a protein in advance. In this thesis, we develop three terms as the materials of the fitness function that can be successfully used in protein backbone structure prediction. In the result of this thesis, it shows that over 80% of good values calculated from our fitness function, which are generated by the genetic programming, are better than the average in the CASP8.
目次 Table of Contents
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Chapter 2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Amino Acids in Proteins . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Levels of Protein Structures . . . . . . . . . . . . . . . . . . . . . . . 4
2.3 Conformational Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.4 Protein Structure Prediction Methods . . . . . . . . . . . . . . . 10
2.5 Sequence Alignment . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.6 Genetic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.7 Root Mean Square Deviation . . . . . . . . . . . . . . . . . . . . . . 17
2.8 Critical Assessment of Protein Structure Prediction . . . . . . . . . . 20
Chapter 3. Our Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Chapter 4. Experimental Results . . . . . . . . . . . . . . . . . . . . . .31
Chapter 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
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