A parallel approach of COFFEE objective function to multiple sequence alignment
نویسندگان
چکیده
منابع مشابه
M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic
Motivation Multiple sequence alignment (MSA) is an NP-complete optimization problem found in computational biology, where the time complexity of finding an optimal alignment raises exponentially along with the number of sequences and their lengths. Additionally, to assess the quality of a MSA, a number of objectives can be taken into account, such as maximizing the sum-of-pairs, maximizing the ...
متن کاملCOFFEE: an objective function for multiple sequence alignments
MOTIVATION In order to increase the accuracy of multiple sequence alignments, we designed a new strategy for optimizing multiple sequence alignments by genetic algorithm. We named it COFFEE (Consistency based Objective Function For alignmEnt Evaluation). The COFFEE score reflects the level of consistency between a multiple sequence alignment and a library containing pairwise alignments of the s...
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We introduce M-Coffee, a meta-method for assembling multiple sequence alignments (MSA) by combining the output of several individual methods into one single MSA. M-Coffee is an extension of T-Coffee and uses consistency to estimate a consensus alignment. We show that the procedure is robust to variations in the choice of constituent methods and reasonably tolerant to duplicate MSAs. We also sho...
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Multiple Objective Programming (MOP) problems have become famous among many researchers due to more practical and realistic implementations. There have been a lot of methods proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP problems by starting from a utopian point (which is usually infeasible) and moving towards the...
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MUSCLE ALGORITHM ABSTRACT We describe MUSCLE, a new program for creating multiple alignments of protein sequences. MUSCLE achieves the highest score so far reported on the BAliBASE benchmark, with average accuracy statistically indistinguishable from T-Coffee. MUSCLE aligns 5,000 sequences of average length 350 in 7 minutes on a current desktop computer, requiring less time than all other teste...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2015
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/633/1/012084