ArticleBioinformatics advances2025
SW-actors: accelerating the Smith-Waterman algorithm via actors.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: The Smith-Waterman (SW) algorithm is widely regarded as the gold standard for local sequence alignment. However, its time complexity in a serial implementation limits its practicality for large datasets. In this article, we introduce SW-actors, a parallel implementation of the SW algorithm that leverages the actor model of concurrent computation to optimize resource utilization by efficiently scheduling and managing independent alignment tasks across processors at both the interalignment and intraalignment levels. Results: SW-actors is compared with the state-of-the-art implementations Parasail, SeqAn, and SWIPE using four datasets of varying sequence lengths ranging from 85 to 74778 nucleotides. In terms of wall-clock time, SW-actors is 1.33 Availability and implementation: The SW-actors source code and underlying data are available at https://git.cs.usask.ca/numerical_simulations_lab/actors/papers/sw-actors.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.