Evidence map›Paper›PMID 32655300›Full record

ArticleCurrent genomics2020

WITMSG: Large-scale Prediction of Human Intronic m

Lian Liu, Xiujuan Lei, Jia Meng, Zhen Wei

Open access · bronzeAbstract read
In one paragraph

Article in Current genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

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  11. Recent advances in functional annotation and prediction of the epitranscriptome.Computational and structural biotechnology journal · 2021
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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

4 authors at 1 institution in 1 country.

Lian Liu1School of Computer Sciences, Shannxi Normal University, Xi'an, Shaanxi, 710119, China; 2Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China.
Xiujuan Lei1School of Computer Sciences, Shannxi Normal University, Xi'an, Shaanxi, 710119, China; 2Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China.
Jia Meng1School of Computer Sciences, Shannxi Normal University, Xi'an, Shaanxi, 710119, China; 2Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China.
Zhen Wei1School of Computer Sciences, Shannxi Normal University, Xi'an, Shaanxi, 710119, China; 2Department of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China.
Xi’an Jiaotong-Liverpool University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMETHODOLOGY: A computational framework, WITMSG, dedicated to the large-scale prediction of intronic m RESULTS AND

conclusionIt has been observed that WITMSG outperformed competing approaches (trained with all the m

Indexed as

genomic featuresintronm6ARNA methylationsequence featuressite prediction

Identifiers

PMID32655300
PMCPMC7324894
OpenAlexW3005695256

What OpenQuestion holds

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LicenceCC BY-NC
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.