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
Hauptverfasser: Zong, Peiyu, Deng, Wenpeng, Liu, Jian, Ruan, Jue
Format: Artikel
Sprache:eng
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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.
ISSN:2709-4715
2709-4715
DOI:10.46471/gigabyte.141