Sequence Alignment Using Nature-Inspired Metaheuristic Algorithms
| Main Authors: | Shahab, Muhammad Luthfi; Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia., Irawan, Mohammad Isa; Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia. |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Institut Teknologi Sepuluh Nopember
, 2017
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| Subjects: | |
| Online Access: |
http://iptek.its.ac.id/index.php/ijcsam/article/view/2118 http://iptek.its.ac.id/index.php/ijcsam/article/view/2118/1719 |
Daftar Isi:
- The most basic process in sequence analysis is sequence alignment, usually solved by dynamic programming Needleman-Wunsch algorithm. However, Needleman-Wunsch algorithm has some lack when the length of the sequence which is aligned is big enough. Because of that, sequence alignment is solved by metaheuristic algorithms. In the present, there are a lot of new metaheuristic algorithms based on natural behavior of some species, we usually call them as nature-inspired metaheuristic algorithms. Some of those algorithm that are more efficient are firefly algorithm, cuckoo search, and flower pollination algorithm. In this research, we use those algorithms to solve sequence alignment. The results show that those algorithms can be used to solve sequence alignment with good result and linear time computation.