| Autor: |
Peiyu Zong, Wenpeng Deng, Jian Liu, Jue Ruan |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
GigaByte (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2709-4715 |
| DOI: |
10.46471/gigabyte.141 |
| Popis: |
The rapid advancements in sequencing length necessitate the adoption of increasingly efficient sequence alignment algorithms. The Needleman–Wunsch method introduces the foundational dynamic-programming matrix calculation for global alignment, which evaluates the overall alignment of sequences. However, this method is known to be highly time-consuming. The proposed TSTA algorithm leverages both vector-level and thread-level parallelism to accelerate pairwise and multiple sequence alignments. Availability and implementation Source codes are available at https://github.com/bxskdh/TSTA. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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