Evidence map›Paper›PMID 28968741›Full record

ArticleBioinformatics (Oxford, England)2017

Kmer-SSR: a fast and exhaustive SSR search algorithm.

Brandon D Pickett, Justin B Miller, Perry G Ridge

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
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  4. The first engkabang jantong (Data in brief · 2025
    Article
  5. Review
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  7. MicrosatNavigator: exploring nonrandom distribution and lineage-specificity of microsatellite repeat motifs on vertebrate sex chromosomes across 186 whole genomes.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Brandon D PickettDepartment of Biology, BYU, Provo, UT 84602, USA.
Justin B MillerDepartment of Biology, BYU, Provo, UT 84602, USA.
Perry G RidgeDepartment of Biology, BYU, Provo, UT 84602, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationOne of the main challenges with bioinformatics software is that the size and complexity of datasets necessitate trading speed for accuracy, or completeness. To combat this problem of computational complexity, a plethora of heuristic algorithms have arisen that report a 'good enough' solution to biological questions. However, in instances such as Simple Sequence Repeats (SSRs), a 'good enough' solution may not accurately portray results in population genetics, phylogenetics and forensics, which require accurate SSRs to calculate intra- and inter-species interactions.

resultsWe present Kmer-SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelized, easy-to-use manner. The exhaustive Kmer-SSR option has 100% precision and 100% recall and accurately identifies every SSR of any specified length. To identify more biologically pertinent SSRs, we also developed several filters that allow users to easily view a subset of SSRs based on user input. Kmer-SSR, coupled with the filter options, accurately and intuitively identifies SSRs quickly and in a more user-friendly manner than any other SSR identification algorithm. AVAILABILITY AND IMPLEMENTATION: The source code is freely available on GitHub at https://github.com/ridgelab/Kmer-SSR. CONTACT: perry.ridge@byu.edu.

Indexed as

AlgorithmsMicrosatellite RepeatsSoftwareComputational Biology

Identifiers

PMID28968741
PMCPMC5860095

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.