Detecting Type and Index Mutation in Cancer DNA Sequence Based on Needleman–Wunsch Algorithm

  • Untari Novia Wisesty Telkom University
  • Tati Rajab Mengko School of Electrical and Information Engineering, Bandung Institute of Technology
  • Ayu Purwarianti School of Electrical and Information Engineering, Bandung Institute of Technology
  • Adi Pancoro School of Life Sciences and Technology, Bandung Institute of Technology
DOI: https://doi.org/10.21609/jiki.v17i2.1273

Abstract

Detecting DNA sequence mutations in cancer patients contributes to early identification and treatment of the disease, which ultimately enhances the effectiveness of treatment. Bioinformatics utilizes sequence alignment as a powerful tool for identifying mutations in DNA sequences. We used the Needleman-Wunsch algorithm to identify mutations in DNA sequence data from cancer patients. The cancer sequence dataset used includes breast, cervix uteri, lung, colon, liver and prostate cancer. Various types of mutations were identified, such as Single Nucleotide Variant (SNV)/substitution, insertion, and deletion, locate by the nucleotide index. The Needleman Wunch algorithm can detect type and index mutation with the average F1-scores 0.9507 for all types of mutations, 0.9919 for SNV, 0.7554 for insertion, and 0.8658 for deletion with a tolerance of 5 bp. The F1-scores obtained are not correlated with gene length. The time required ranges from 1.03 seconds for a 290 base pair gene to 3211.45 seconds for a gene with 16613 base pairs.

Published
2024-06-03
How to Cite
Wisesty, U. N., Mengko, T. R., Purwarianti, A., & Pancoro, A. (2024). Detecting Type and Index Mutation in Cancer DNA Sequence Based on Needleman–Wunsch Algorithm. Jurnal Ilmu Komputer Dan Informasi, 17(2), 167-174. https://doi.org/10.21609/jiki.v17i2.1273
Issue
Vol. 17 No. 2 (2024): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Section
Articles

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