Using guide trees to construct multiple-sequence evolutionary HMMs
Using guide trees to construct multiple-sequence evolutionary HMMs
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DOI：
10.1093/bioinformatics/btg1019
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发表时间：
2003-07-01
期刊：
影响因子：
5.8
通讯作者：
Holmes, I.
中科院分区：
文献类型：
--
作者：
Holmes, I.
动机：基于分数的渐进式比对算法在指导树的连续分支上进行动态编程。类似的概率构造是演化HMM。这是一个多序列隐马尔可夫模型（HMM）的组合传感器（条件归一化对HMM）的分支上的系统发育树。方法：我们提出了一般的算法，用于构建一个进化的HMM从任何对HMM和动态规划任何多序列HMM。结果：我们的原型实现，亨德尔，是基于索恩-岸野-Felsenstein进化模型和基准使用结构参考比对。
Motivation: Score-based progressive alignment algorithms do dynamic programming on successive branches of a guide tree. The analogous probabilistic construct is an Evolutionary HMM. This is a multiple-sequence hidden Markov model (HMM) made by combining transducers (conditionally normalised Pair HMMs) on the branches of a phylogenetic tree.Methods: We present general algorithms for constructing an Evolutionary HMM from any Pair HMM and for doing dynamic programming to any Multiple-sequence HMM.Results: Our prototype implementation, Handel, is based on the Thorne-Kishino-Felsenstein evolutionary model and is benchmarked using structural reference alignments.