Abstract
Top-k similar sequence search is an essential tool for DNA data management. Given a DNA database, it is a problem to extract k similar DNA sequence pairs in the database, which yield the highest similarity among all possible pairs. Although this is a fundamental problem used in the bioinformatics field, it suffers from an expensive computational cost. To overcome these limitations, we propose a novel fast top-k similarity search algorithm for DNA databases. We conducted experiments using real-world DNA sequence datasets, and experimentally confirmed that the proposed method achieves a faster top-k search than baseline algorithms while keeping high accuracy.
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Yagi, R., Shiokawa, H. (2022). Fast Top-k Similar Sequence Search on DNA Databases. In: Pardede, E., Delir Haghighi, P., Khalil, I., Kotsis, G. (eds) Information Integration and Web Intelligence. iiWAS 2022. Lecture Notes in Computer Science, vol 13635. Springer, Cham. https://doi.org/10.1007/978-3-031-21047-1_14
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DOI: https://doi.org/10.1007/978-3-031-21047-1_14
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