ArticleNucleic acids research2013
MsDetector: toward a standard computational tool for DNA microsatellites detection.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed, 25 citations in OpenAlex.
- What are microsatellites and how to choose the best tool: a user-friendly review of SSR and 74 SSR mining tools.Frontiers in genetics · 2024Review
- MegaSSR: a web server for large scale microsatellite identification, classification, and marker development.Frontiers in plant science · 2023Article
- Analysis of repeat elements in the Pristionchus pacificus genome reveals an ancient invasion by horizontally transferred transposons.BMC genomics · 2022Article
- Article
- BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data.Frontiers in big data · 2021Article
- Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types.Genome research · 2020Article
- Dot2dot: accurate whole-genome tandem repeats discovery.Bioinformatics (Oxford, England) · 2019Article
- SSRome: an integrated database and pipelines for exploring microsatellites in all organisms.Nucleic acids research · 2019Article
- MeShClust: an intelligent tool for clustering DNA sequences.Nucleic acids research · 2018Article
- Red: an intelligent, rapid, accurate tool for detecting repeats de-novo on the genomic scale.BMC bioinformatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Microsatellites (MSs) are DNA regions consisting of repeated short motif(s). MSs are linked to several diseases and have important biomedical applications. Thus, researchers have developed several computational tools to detect MSs. However, the currently available tools require adjusting many parameters, or depend on a list of motifs or on a library of known MSs. Therefore, two laboratories analyzing the same sequence with the same computational tool may obtain different results due to the user-adjustable parameters. Recent studies have indicated the need for a standard computational tool for detecting MSs. To this end, we applied machine-learning algorithms to develop a tool called MsDetector. The system is based on a hidden Markov model and a general linear model. The user is not obligated to optimize the parameters of MsDetector. Neither a list of motifs nor a library of known MSs is required. MsDetector is memory- and time-efficient. We applied MsDetector to several species. MsDetector located the majority of MSs found by other widely used tools. In addition, MsDetector identified novel MSs. Furthermore, the system has a very low false-positive rate resulting in a precision of up to 99%. MsDetector is expected to produce consistent results across studies analyzing the same sequence.
Indexed as
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.