序列比對在計算生物學上是一個基本的方法，其基本功用是藉由生物序列上的差異大小比對出序列在演化過程中距離的遠近，然後再藉此結果加以應用。
傳統上，蛋白質序列比對只應用到蛋白質一級結構的資訊，而沒有考慮到二級結構的重要性，本篇論文的重點即是藉由增加二級結構的資訊來增加序列比對的意義。再者，在同源模擬法(homology modeling)中，其決定性的步驟在於找到一個相似的已知結構，並且以此為基礎來預測未知的蛋白質結構，本論文希望能夠改進傳統序列比對的方法，找出蛋白質一級結構相似程度較低，但是其二級結構相似度較高的蛋白質用來當作結構預測的模板。

Sequence alignment is a basic but powerful technique in molecular biology.
Macromolecular sequences (DNA, RNA and protein sequences) can be aligned based
on some criteria. The goal of sequence alignment is to find the similarity and the
difference of input sequences. With various purposes, there are different algorithms
In this thesis, we present a new algorithm which aligns sequences with consideration of secondary structures. Traditionally, a sequence alignment algorithm
considers only the primary structure, which is the amino acid chain. When we make
use of the information of protein secondary structure such as alpha helix, beta sheet etc,
the sensitivity of pairwise alignment can be improved.

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0
Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 DNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 RNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Sequence Alignment . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Chapter 2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1 Dynamic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Scoring Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Scoring Matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4 DNA Sequence Alignment . . . . . . . . . . . . . . . . . . . . . . . . 13
2.5 Protein Sequence Alignment . . . . . . . . . . . . . . . . . . . . . . . 17
Chapter 3. Protein Structure Prediction . . . . . . . . . . . . . . . . . 21
3.1 Determination of Structures of Proteins . . . . . . . . . . . . . . . . . 21
3.2 Prediction of Protein Structures . . . . . . . . . . . . . . . . . . . . . 23
Chapter 4. Our Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Page
4.1 Secondary Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.2 A Novel Sequence Alignment Algorithm . . . . . . . . . . . . . . . . 29
Chapter 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Appendixes
A. Score Matrix of Secondary Structure . . . . . . . . . . . . . . . . . . 40
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

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