在這篇論文當中我們設計了一個演算法，稱為「在有限制情況下的多重序列排比」，由於之前的多重序列排比方法不一定能夠滿足生物學家的需求，特別是某些被認定應該必須排比在一起的字元。所以我們設計了一個方法能夠滿足生物學家所認定必須排比在一起的字元。首先我們先設計了一個三維空間動態程式設計的方法來產生在有限制情況下時兩條序列的排比，接著我們再使用Feng and Doolittle [8]所提逐步排比的方法(progressive alignment approach)，對所有的序列做任兩條有限制的序列排比，利用此結果建立一個距離矩陣(distance matrix)，然後根據距離矩陣中序列的相似程度利用Kruskal演算法來建立最小擴張樹。最後根據Kruskal找尋最小擴張樹的順序逐一合併所有的兩條序列排比，形成有的限制多重序列排比。在我們的實驗之下，證明了我們的方法能夠的將生物學家所提出的限制條件，完全的排比在一起。而我們演算法的時間複雜度，在K條序列下為需花O(Kn4)，其中n為所有序列中的最大長度。所以我們的方法可算是一個不錯的方法。

We design a new algorithm of computing constrained multiple sequence alignment (CMSA) for guaranteeing that generated alignment satisfies the user- specified constraints that some particular residues should be aligned together. The first step of our strategy is design a constrained pairwise sequence alignment. Next, based on the concept of progressive alignment, we use the constrained pairwise sequence alignment to progressively merge the sequences. The time complexity of our CMSA algorithm for aligning K sequences is O(Kn4),where n is the maximum of lengths of sequences. We experimented our algorithm on RNases sequences with known structure and results of our experiment are all the important residues of active sites are well aligned together.

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