Open AccessEstimation of Super Pairwise Alignment (SPA) parameters on zika virus mutation using Artificial Bee Colony
Author(s) -
Dinita Rahmalia,
Arif Rohmatullah,
Mohammad Syaiful Pradana
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1417/1/012029
Subject(s) - pairwise comparison , zika virus , similarity (geometry) , mutation , computer science , penalty method , artificial intelligence , virus , mathematical optimization , biology , mathematics , virology , genetics , gene , image (mathematics)
There are many diseases caused by viruses or bacteria. The structure of virus and bacteria always mutate to create new structures. Sequence alignment is important so that it can be used to research genetic diseases and epidemics. In this reseach, we take case study of zika virus. To see the similarity between original virus and the mutation virus, it is required the alignment process of two virus sequences. The method used for aligning two virus sequences is Super Pairwise Alignment (SPA). Due to the value of objective function depends on SPA parameters, in this research we will apply heuristic method, such as Artificial Bee Colony (ABC) algorithm to optimize SPA parameters minimizing penalty value or maximizing similarity value as objective function. ABC is the optimization method which is inspired by the behaviour of bee colony in which the advantages are there are three types of bees that will update optimal solution in approaching. From the ABC simulations, we can obtain optimal SPA parameters resulting minimum penalty value or maximum similarity value between two aligned zika virus protein sequences in approaching.