The Performance Assessment Strategy in DC-BTA Multiple Sequence Alignment

2010 ◽  
Vol 439-440 ◽  
pp. 35-40
Author(s):  
Zhan Mao Cao ◽  
Wen Jun Xiao ◽  
Li Min Peng

A brand new performance assessment model is proposed for multiple sequence alignment. The new strategy is based on beam constructing of DC-BTA algorithm, which is a Divide-and-Conquer alignment method with beams. Beams form blocks of almost the identical columns and contribute biggest similarity weight to sequences. A formula to compute all beam areas covering a sequence assigns a value or weight to the sequence. And the total beam area is a partial to the whole alignment. A rate value between 0 and 1 is computed to assess the performance. This scheme is a simple and effective assessment policy in DC-BTA for the convenience of collecting the beam areas.

2014 ◽  
Vol 23 (3) ◽  
pp. 261-275 ◽  
Author(s):  
Widad Kartous ◽  
Abdesslem Layeb ◽  
Salim Chikhi

AbstractMultiple sequence alignment (MSA) is one of the major problems that can be encountered in the bioinformatics field. MSA consists in aligning a set of biological sequences to extract the similarities between them. Unfortunately, this problem has been shown to be NP-hard. In this article, a new algorithm was proposed to deal with this problem; it is based on a quantum-inspired cuckoo search algorithm. The other feature of the proposed approach is the use of a randomized progressive alignment method based on a hybrid global/local pairwise algorithm to construct the initial population. The results obtained by this hybridization are very encouraging and show the feasibility and effectiveness of the proposed solution.


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