Evidence map›Paper›PMID 26184875›Full record

ArticleNucleic acids research2015

STAR3D: a stack-based RNA 3D structural alignment tool.

Ping Ge, Shaojie Zhang

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. 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

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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. WebSTAR3D: a web server for RNA 3D structural alignment.Bioinformatics (Oxford, England) · 2016
    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

2 authors.

Ping GeDepartment of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA.
Shaojie ZhangDepartment of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA shzhang@eecs.ucf.edu.

Funding

RNA Structural Motif Analysis Revisited: Towards a Systematic Understanding of Noncoding RNA as Modular BiomoleculesR01GM102515 · NIGMS · UNIVERSITY OF CENTRAL FLORIDA · PI ZHANG, SHAOJIE, ZHONG, CUNCONG · 2012 to 2025
$2.3M
NIGMS NIH HHS R01 GM102515NIGMS NIH HHS R01GM102515
6 · The paper itself

Abstract

The various roles of versatile non-coding RNAs typically require the attainment of complex high-order structures. Therefore, comparing the 3D structures of RNA molecules can yield in-depth understanding of their functional conservation and evolutionary history. Recently, many powerful tools have been developed to align RNA 3D structures. Although some methods rely on both backbone conformations and base pairing interactions, none of them consider the entire hierarchical formation of the RNA secondary structure. One of the major issues is that directly applying the algorithms of matching 2D structures to the 3D coordinates is particularly time-consuming. In this article, we propose a novel RNA 3D structural alignment tool, STAR3D, to take into full account the 2D relations between stacks without the complicated comparison of secondary structures. First, the 3D conserved stacks in the inputs are identified and then combined into a tree-like consensus. Afterward, the loop regions are compared one-to-one in accordance with their relative positions in the consensus tree. The experimental results show that the prediction of STAR3D is more accurate for both non-homologous and homologous RNAs than other state-of-the-art tools with shorter running time.

Indexed as

SoftwareModels, MolecularNucleic Acid ConformationRNA, Ribosomal, 16SRNA, Ribosomal, 23SRNA, UntranslatedRNA, Ribosomal, 16SRNA, Ribosomal, 23SRNA, Untranslated

Identifiers

PMID26184875
PMCPMC4787758

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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.