ArticleBioinformatics advances2026
FroM Superstring to Indexing: a space-efficient index for unconstrained
Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- RSHash: a fast and space-efficient hash table for k-mers.Bioinformatics (Oxford, England) · 2026Article
- Optimizing sparse and skew hashing: faster k-mer dictionaries.Bioinformatics (Oxford, England) · 2026Article
- Optimizing sparse and skew hashing: fasterbioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: The growing volumes and heterogeneity of genomic data call for scalable and versatile Results: We introduce FMSI, a superstring-based index for arbitrary Availability and implementation: FMSI is developed in C++ and released under the MIT license, with source code provided at https://github.com/OndrejSladky/fmsi and an installable package available through Bioconda. The datasets used in the experiments are deposited at Zenodo (https://doi.org/10.5281/zenodo.14722244).
Identifiers
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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.