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Application Bat Algorithm for Estimating Super Pairwise Alignment Parameters on Similarity Analysis Between Virus Protein Sequences

Dinita Rahmalia, Teguh Herlambang

Abstract


There were many diseases caused by viruses or bacteria. the virus or bacteria can mutate so that they could result the new disease. Sequence alignment was important so that it could be used to research genetic diseases and epidemics. In this reseach, we took case study of dengue virus and zika virus. To see the similarity between original virus and the mutation virus, it wass required the alignment process of two virus sequences. The method used for aligning two virus sequences was Super Pairwise Alignment (SPA). Due to the similarity value depended on SPA parameters, in this research we would apply heuristic method, such as Bat Algorithm (BA) algorithm to optimize SPA parameters maximizing similarity value as objective function. BA was the optimization method which was inspired by the behavior of bats in using sonar called echolocation to detect prey, avoid obstacles. From the BA simulations, we could obtain optimal SPA parameters resulting maximum similarity value between two aligned each of dengue virus and zika virus protein sequences in approaching.

Keywords


Parameter estimation; Super Pairwise Alignment; Sequence Alignment; Bat Algorithm; Similarity Analysis

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References


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DOI: http://dx.doi.org/10.26555/jiteki.v6i2.14323

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