TSTA: thread and SIMD-based trapezoidal pairwise/multiple sequence-alignment method
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. Howev...
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Veröffentlicht in: | GigaByte (Hong Kong, China) China), 2024-11, Vol.2024, p.gigabyte141 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | 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.
Source codes are available at https://github.com/bxskdh/TSTA. |
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ISSN: | 2709-4715 2709-4715 |
DOI: | 10.46471/gigabyte.141 |