Shahab, Muhammad Luthfi (2017) Multiple Sequence Alignment Menggunakan Nature-Inspired Metaheuristic Algorithms. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Multiple sequence alignment adalah proses dasar yang sering dibutuhkan dalam mengolah beberapa sequence yang berhubungan dengan bioinformatika. Apabila multiple sequence alignment telah selesai dikerjakan, maka dapat dilakukan analisis-analisis lain yang lebih jauh, seperti analisis filogenetik atau prediksi struktur protein. Banyaknya kegunaan dari multiple sequence alignment mengakibatkannya menjadi salah satu permasalahan yang banyak diteliti. Banyak algoritma-algoritma metaheuristic yang berdasar pada kejadian-kejadian alami, yang biasa disebut dengan nature-inspired metaheuristic algorithms. Beberapa algoritma baru dalam nature-inspired metaheuristic algorithms yang dianggap cukup efisien antara lain adalah firefly algorithm, cuckoo search, dan flower pollination algorithm. Dalam penelitian ini dipaparkan modified Needleman-Wunsch alignment. Didapatkan hasil bahwa modified Needleman-Wunsch alignment adalah metode yang cukup bagus. Modified Needleman-Wunsch alignment tersebut digunakan untuk membentuk solusi awal dari firefly algorithm, cuckoo search, dan flower pollination algorithm. Didapatkan hasil bahwa firefly algorithm, cuckoo search, dan flower pollination algorithm dapat menghasilkan solusi-solusi baru yang lebih baik. Secara keseluruhan, firefly algorithm adalah algoritma yang terbaik dari tiga algoritma tersebut dalam segi skor alignment, namun membutuhkan waktu komputasi yang lebih besar.
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Multiple sequence alignment is a fundamental tool that often needed to process bioinformatic sequences. If multiple sequence alignment is completed, we can process other further analysis, such as phylogenetic analysis or protein structure prediction. The versatility of multiple sequence alignment led it to be the one of the problems that studied continously. Many metaheuristic algorithms are based on natural events, with the so called nature-inspired metaheuristic algorithms. Algorithms in nature-inspired metaheuristic algorithms that considered to be good are firefly algorithm, cuckoo search, and flower pollination algorithm. In this research, we propose modified Needleman-Wunsch alignment. The results show that modified Needleman-Wunsch alignment is a good method. Modified Needleman-Wunsch alignment is used to create initial solution of firefly algorithm, cuckoo search, and flower pollination algorithm. The results show that firefly algorithm, cuckoo search, and flower pollination algorithm can produce new better solution. Overall, firefly algorithm is the best algorithm among the others in alignment score, but need large computation time.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | multiple sequence alignment, modified Needleman-Wuncsh alignment, firefly algorithm, cuckoo search, flower pollination algorithm |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science. EDP |
| Divisions: | Faculty of Mathematics and Science > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | MUHAMMAD LUTHFI SHAHAB |
| Date Deposited: | 04 Apr 2017 03:10 |
| Last Modified: | 06 Mar 2019 03:50 |
| URI: | http://repository.its.ac.id/id/eprint/2876 |
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