關於如何預測RNA的二級結構，在計算生物學中是一個廣泛研究的問題，然而目前所有現有的預測演算法都是基於一個假設:所有的核甘酸只允許和一個核甘酸有氫鍵連結產生鹼基對(base pair)。但是對於目前已知的triple helix結構（一個pseudoknot型的的結構中有允許兩個或以上的核甘酸互相產生鍵結產生tertiary interaction）來說，他的結構違反了這個假設。另一方面最近的研究顯示這種類型的結構在許多的生物的反應過程中扮演了重要的角色。因此創造一個如何預測triple helix結構的預測工具是十分有價值的。我們提供了第一個對於triple helix結構的預測演算法，我們的演算法的時間複雜度是O(n3)，其中n是代表了這條RNA的核甘酸數目。我們的演算法的預測準確度中對鹼基對的靈敏度(sensitivity)和特異度(specificity)都超過80%，而對tertiary interaction的準確度兩個也都超過了70%，這兩個結果對於目前還沒有一個適合的演算法來預測triplex helix結構來說是一個新的突破。

Secondary structure prediction of an RNA molecule is an important but challenging computational problem, in particular when the structure contains pseudoknots. Most existing algorithms target at restricted pseudoknot structures. However, all these algorithms have an assumption that each nucleotide can interact with at most one nucleotide. This assumption is not valid for triple helix structure (a pseudoknotted structure with tertiary in-
teraction).
In this thesis, we provide the rst structural prediction solution to handle these tertiary interactions. Our algorithm runs in O(n3) time. The accuracy of the prediction is reasonably high, with average sensitivity and specicity over 80% for base pairs, and over 70% for tertiary interactions.

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