Evidence map›Paper›PMID 33760053›Full record

ArticleBioinformatics (Oxford, England)2021

STREME: accurate and versatile sequence motif discovery.

Timothy L Bailey

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 390 papers.

0numbers the graph read from it
0cells of the map it votes in
390citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

390 citing papers in PubMed.

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  10. Regulatory logic of neuronal differentiation in theProceedings of the National Academy of Sciences of the United States of America · 2026
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  15. Honeydew: A Fluorescent Aptamer for Low-Cost Azo Food Dyes.Chembiochem : a European journal of chemical biology · 2026
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330 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

1 author.

Timothy L BaileyDepartment of Pharmacology, University of Nevada, Reno, NV 89557, USA.ORCID 0000-0002-7018-9342

Funding

The MEME Suite of motif-based sequence analysis toolsR01GM103544 · NIGMS · UNIVERSITY OF WASHINGTON · PI BAILEY, TIMOTHY L · 2012 to 2020
$2.4M
NIGMS NIH HHS R01 GM103544
6 · The paper itself

Abstract

motivationSequence motif discovery algorithms can identify novel sequence patterns that perform biological functions in DNA, RNA and protein sequences-for example, the binding site motifs of DNA- and RNA-binding proteins.

resultsThe STREME algorithm presented here advances the state-of-the-art in ab initio motif discovery in terms of both accuracy and versatility. Using in vivo DNA (ChIP-seq) and RNA (CLIP-seq) data, and validating motifs with reference motifs derived from in vitro data, we show that STREME is more accurate, sensitive and thorough than several widely used algorithms (DREME, HOMER, MEME, Peak-motifs) and two other representative algorithms (ProSampler and Weeder). STREME's capabilities include the ability to find motifs in datasets with hundreds of thousands of sequences, to find both short and long motifs (from 3 to 30 positions), to perform differential motif discovery in pairs of sequence datasets, and to find motifs in sequences over virtually any alphabet (DNA, RNA, protein and user-defined alphabets). Unlike most motif discovery algorithms, STREME reports a useful estimate of the statistical significance of each motif it discovers. STREME is easy to use individually via its web server or via the command line, and is completely integrated with the widely used MEME Suite of sequence analysis tools. The name STREME stands for 'Simple, Thorough, Rapid, Enriched Motif Elicitation'. AVAILABILITY AND IMPLEMENTATION: The STREME web server and source code are provided freely for non-commercial use at http://meme-suite.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsSoftwareBinding SitesChromatin Immunoprecipitation SequencingDNANucleotide MotifsSequence Analysis, DNADNA

Identifiers

PMID33760053
PMCPMC8479671

What OpenQuestion holds

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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.