Evidence map›Paper›PMID 24396270›Full record

ArticleCurrent genomics2013

Computational approaches in detecting non- coding RNA.

Chunyu Wang, Leyi Wei, Maozu Guo, Quan Zou

Abstract read
In one paragraph

Article in Current genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  4. Review
  5. Key players in regulatory RNA realm of bacteria.Biochemistry and biophysics reports · 2022
    Review
  6. Prokaryotic ncRNAs: Master regulators of gene expression.Current research in pharmacology and drug discovery · 2022
    Article
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  17. Survey of Natural Language Processing Techniques in Bioinformatics.Computational and mathematical methods in medicine · 2015
    Review
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

4 authors.

Chunyu WangSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
Leyi WeiSchool of Information Science and Technology, Xiamen University, Xiamen 361005, China.
Maozu GuoSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
Quan ZouSchool of Information Science and Technology, Xiamen University, Xiamen 361005, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The important role of non coding RNAs (ncRNAs) in the cell has made their identification a critical issue in the biological research. However, traditional approaches such as PT-PCR and Northern Blot are costly. With recent progress in bioinformatics and computational prediction technology, the discovery of ncRNAs has become realistically possible. This paper aims to introduce major computational approaches in the identification of ncRNAs, including homologous search, de novo prediction and mining in deep sequencing data. Furthermore, related software tools have been compared and reviewed along with a discussion on future improvements.

Indexed as

BioinformaticsDeep sequencing.lncRNAMachine learningmicroRNANon-coding RNA

Identifiers

PMID24396270
PMCPMC3861888

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.