ArticleGenome biology2026
Multi-context seeds enable fast and high-accuracy read mapping.
Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed.
- Sassy: fuzzy searching DNA sequences using SIMD.Bioinformatics (Oxford, England) · 2026Article
- Multi-context seeds enable fast and high-accuracy read mapping.Genome biology · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
A key step in sequence similarity search is to identify shared seeds between a query and a reference sequence. A well-known tradeoff is that longer seeds offer fast searches but reduce sensitivity in variable regions. We introduce multi-context seeds (MCS), which allow the storage of seeds with different lengths in the same index structure, thus retaining the advantages of both short and long seeds. We demonstrate the applicability of MCS by implementing them in strobealign. Strobealign with MCS substantially improves accuracy compared to the previous version with little cost in runtime and no memory overhead.
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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.