Evidence map›Paper›PMID 23991010›Full record

ArticlePloS one2013

Predicting helical topologies in RNA junctions as tree graphs.

Christian Laing, Segun Jung, Namhee Kim, Shereef Elmetwaly, Mai Zahran, Tamar Schlick

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. RNA 3D Structure Prediction Using Coarse-Grained Models.Frontiers in molecular biosciences · 2021
    Review
  8. Article
  9. Article
  10. Article
  11. Adventures with RNA graphs.Methods (San Diego, Calif.) · 2018
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Integer sequence discovery from small graphs.Discrete applied mathematics (Amsterdam, Netherlands : 1988) · 2016
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

6 authors.

Christian LaingDepartment of Biology, Wilkes University, Wilkes-Barre, Pennsylvania, United States of America ; Department of Mathematics and Computer Science, Wilkes University, Wilkes-Barre, Pennsylvania, United States of America.
Segun Jung
Namhee Kim
Shereef Elmetwaly
Mai Zahran
Tamar Schlick

Funding

Modeling RNA Tertiary Structure Folding by a Hierarchical FrameworkR01GM100469 · NIGMS · NEW YORK UNIVERSITY · PI SCHLICK, TAMAR · 2011 to 2014
$1.5M
Computational studies of in vitro selection of RNAsR01GM081410 · NIGMS · NEW YORK UNIVERSITY · PI SCHLICK, TAMAR · 2009 to 2012
$1.2M
NIGMS NIH HHS GM081410NIGMS NIH HHS GM100469NIGMS NIH HHS R01 GM081410NIGMS NIH HHS R01 GM100469
6 · The paper itself

Abstract

RNA molecules are important cellular components involved in many fundamental biological processes. Understanding the mechanisms behind their functions requires knowledge of their tertiary structures. Though computational RNA folding approaches exist, they often require manual manipulation and expert intuition; predicting global long-range tertiary contacts remains challenging. Here we develop a computational approach and associated program module (RNAJAG) to predict helical arrangements/topologies in RNA junctions. Our method has two components: junction topology prediction and graph modeling. First, junction topologies are determined by a data mining approach from a given secondary structure of the target RNAs; second, the predicted topology is used to construct a tree graph consistent with geometric preferences analyzed from solved RNAs. The predicted graphs, which model the helical arrangements of RNA junctions for a large set of 200 junctions using a cross validation procedure, yield fairly good representations compared to the helical configurations in native RNAs, and can be further used to develop all-atom models as we show for two examples. Because junctions are among the most complex structural elements in RNA, this work advances folding structure prediction methods of large RNAs. The RNAJAG module is available to academic users upon request.

Indexed as

Models, MolecularNucleic Acid ConformationRNA FoldingBase SequenceComputational BiologyMolecular Sequence DataReproducibility of ResultsRNARNA

Identifiers

PMID23991010
PMCPMC3753280

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.