A sequence alignment algorithm with an arbitrary gap penalty function
A sequence alignment algorithm with an arbitrary gap penalty function
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DOI：
10.1089/106652701300312931
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发表时间：
2001-01-01
影响因子：
1.7
通讯作者：
Dewey, TG
中科院分区：
文献类型：
--
作者：
Dewey, TG
本文提出了一种生物序列比对算法，它是生物聚合物统计力学中序列生成函数方法的一种改进。该算法使用由比对概率的配分函数形式发展而来的递归关系，它是在一种动态规划格式中实现的，与隐马尔可夫模型（HMM）中使用的前向算法非常相似，该算法根据统计上占优势的比对路径来比对序列或结构，并且将被称为SDP算法。这种方法优于以前的方法的一个优点是，它允许更复杂和物理上现实的差距罚函数以一种简便的方式纳入算法。该算法的性能在一个案例研究的重链和轻链的可变区的免疫球蛋白进行了研究。
An algorithm for aligning biological sequences is presented that is an adaptation of the sequence generating function approach used in the statistical mechanics of biopolymers, This algorithm uses recursion relationships developed from a partition function formalism of alignment probabilities, It is implemented within a dynamic programming format that closely resembles the forward algorithm used in hidden Markov models (HMM), The algorithm aligns sequences or structures according to the statistically dominant alignment path and will be referred to as the SDP algorithm. An advantage of this method over previous ones is that it allows more complicated and physically realistic gap penalty functions to be incorporated into the algorithm in a facile manner. The performance of this algorithm in a case study of aligning the heavy and light chain from the variable region of an immunoglobulin is investigated.