在人類基因組計劃揭開基因序列後，單倍體是一種對於遺傳疾病研究、藥物目標預測研究上都非常具有助益的資訊，但要用臨床實驗的方法得到單倍體的資訊是非常耗時間而且在經濟上也是一大考驗，所以近年來越來越多的研究是想要從電腦模擬推斷出單倍體的資訊，希望藉由這種方式去加快得到單倍體的資訊。在這篇論文裡，推斷正確單倍體資訊的問題中，我們提出藉由導入多個單核苷酸多態性之間的相互關聯性資訊到成長樹的解決方式裡，經過這樣的方法，我們確實在推斷準確率上得到相較於簡約樹成長法最高至2.62%的成長，且在推斷正確單倍體的問題上，最高的推斷準確率達到95.2%。藉由高準確率的推斷單倍體後，我們希望可以跳過臨床實驗去取得單倍體資訊的步驟，直接拿來幫助其他相關研究。

Haplotypes are a kind of powerful information that is helpful in gene candidate studies because of inheritance characteristics. However, in order to get the haplotype information, in vitro methods cost lots of time and money, it is helpful to infer haplotypes using in Silico methods. Because the haplotype inference is a NP-Hard problem, both the accuracy and computational time are important issues. In this thesis, we take into account of the normalized mutual information in the parsimonious tree-grow methods that show very good performance on haplotype inference problems. And we improve the inference accuracy rate most to 2.62 percent on APOE gene dataset which just spend about 0.001 more seconds than original parsimonious tree-grow method. We also have the highest to 95.2% accuracy rate on β2AR gene data in comparison to previous approaches.

摘要 I
Abstract II
Chapter 1 Introduction 1
Chapter 2 Haplotype Inference Problem 4
Chapter 3 Related Research 6
3.1 Parsimonious tree-grow method 6
3.2 Linkage Disequilibrium 8
Chapter 4 Method 11
4.1 Stage 1. Initialization 11
4.2 Stage 2. Add linkage disequilibrium information into tree-grow procedure 13
4.3 Stage 3. Collect all haplotypes inferred from algorithm 19
4.4 Trying add family’s information into genotypes dataset 20
Chapter 5 Experimental Data 22
5.1 Datasets 22
5.2 Procedure of generating genotypes 23
Chapter 6 Evaluation 24
6.1 Accuracy Rate 24
6.2 Experiment on β2AR gene data 24
6.3 Experiment on Maize data (Acetyl-CoAC-acyltransferase) 25
6.4 Experiment on APOE gene data 25
6.5 Experiment on CYP19 gene data 26
6.6 Experiment on CYP19 gene data with family information 27
Chapter 7 Conclusions and Future Work 28
7.1 Conclusions 28
7.2 Future Work 29
References 30

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