Evidence map›Paper›PMID 25015992›Full record

ArticleBioinformatics (Oxford, England)2014

A new approach for detecting riboswitches in DNA sequences.

Jessen T Havill, Chinmoy Bhatiya, Steven M Johnson, Joseph D Sheets, Jeffrey S Thompson

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

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

13 citing papers in PubMed.

  1. Review
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  7. Riboflow: Using Deep Learning to Classify Riboswitches With ∼99% Accuracy.Frontiers in bioengineering and biotechnology · 2020
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  12. Review
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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

5 authors.

Jessen T HavillDepartment of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.
Chinmoy BhatiyaDepartment of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.
Steven M JohnsonDepartment of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.
Joseph D SheetsDepartment of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.
Jeffrey S ThompsonDepartment of Mathematics and Computer Science, Department of Biology, Denison University, Granville, OH 43023, Capco, New York, NY, 10005, Department of Computer Science, Wake Forest University, Winston-Salem, NC 27109 and College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationRiboswitches are short sequences of messenger RNA that can change their structural conformation to regulate the expression of adjacent genes. Computational prediction of putative riboswitches can provide direction to molecular biologists studying riboswitch-mediated gene expression.

resultsThe Denison Riboswitch Detector (DRD) is a new computational tool with a Web interface that can quickly identify putative riboswitches in DNA sequences on the scale of bacterial genomes. Riboswitch descriptions are easily modifiable and new ones are easily created. The underlying algorithm converts the problem to a 'heaviest path' problem on a multipartite graph, which is then solved using efficient dynamic programming. We show that DRD can achieve ∼ 88-99% sensitivity and >99.99% specificity on 13 riboswitch families. AVAILABILITY AND IMPLEMENTATION: DRD is available at http://drd.denison.edu.

Indexed as

RiboswitchAlgorithmsSequence Analysis, DNASoftwareRiboswitch

Identifiers

PMID25015992
PMCPMC4609007

What OpenQuestion holds

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Registered trials

None linked

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.