Evidence map›Paper›PMID 20927402›Full record

ArticlePloS one2010

Adjacent nucleotide dependence in ncRNA and order-1 SCFG for ncRNA identification.

Thomas K F Wong, Tak-Wah Lam, Wing-Kin Sung, Siu-Ming Yiu

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 2 countries.

Thomas K F WongDepartment of Computer Science, The University of Hong Kong, Hong Kong, Special Administrative Region, People's Republic of China. kfwong@cs.hku.hk
Tak-Wah Lam
Wing-Kin Sung
Siu-Ming Yiu
University of Hong Kong · HKNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-coding RNAs (ncRNAs) are known to be involved in many critical biological processes, and identification of ncRNAs is an important task in biological research. A popular software, Infernal, is the most successful prediction tool and exhibits high sensitivity. The application of Infernal has been mainly focused on small suspected regions. We tried to apply Infernal on a chromosome level; the results have high sensitivity, yet contain many false positives. Further enhancing Infernal for chromosome level or genome wide study is desirable. METHODOLOGY: Based on the conjecture that adjacent nucleotide dependence affects the stability of the secondary structure of an ncRNA, we first conduct a systematic study on human ncRNAs and find that adjacent nucleotide dependence in human ncRNA should be useful for identifying ncRNAs. We then incorporate this dependence in the SCFG model and develop a new order-1 SCFG model for identifying ncRNAs.

conclusionsWith respect to our experiments on human chromosomes, the proposed new model can eliminate more than 50% false positives reported by Infernal while maintaining the same sensitivity. The executable and the source code of programs are freely available at http://i.cs.hku.hk/~kfwong/order1scfg.

Indexed as

Base SequenceComputational BiologyHumansMolecular Sequence DataNucleic Acid ConformationNucleotidesRNA, UntranslatedNucleotidesRNA, Untranslated

Identifiers

PMID20927402
PMCPMC2946929
OpenAlexW2049458147

What OpenQuestion holds

Textmetadata
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.