Improving multiple sequence alignment by using better guide trees
نویسندگان
چکیده
منابع مشابه
Evolving Guide Trees in Progressive Multiple Sequence Alignment
We present a novel application of genetic algorithms to the problem of aligning multiple biological sequences through the optimization of guide trees. Individual guide trees are represented as coalescing binary trees which provide for efficient and meaningful crossover and mutation operations. We hypothesize that our technique avoids the limitations of other heuristic tree-building techniques, ...
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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 constructin...
متن کاملPSAR-Align: improving multiple sequence alignment using probabilistic sampling
SUMMARY We developed PSAR-Align, a multiple sequence realignment tool that can refine a given multiple sequence alignment based on suboptimal alignments generated by probabilistic sampling. Our evaluation demonstrated that PSAR-Align is able to improve the results from various multiple sequence alignment tools. AVAILABILITY AND IMPLEMENTATION The PSAR-Align source code (implemented mainly in ...
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Multiple alignments of biological nucleic acid sequences are one of the most commonly used techniques in sequence analysis. These techniques demand a big computational load. We present a Genetic Algorithms (GA) that optimizes an objective function that is a measure of alignment quality (distance). Each individual in the population represents (in an efficient way) some underlying operations on t...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2015
ISSN: 1471-2105
DOI: 10.1186/1471-2105-16-s5-s4