Evidence map›Paper›PMID 39296930›Full record

ArticleNAR genomics and bioinformatics2024

Evaluation of machine learning models that predict lncRNA subcellular localization.

Jason R Miller, Weijun Yi, Donald A Adjeroh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NAR genomics and bioinformatics, 2024. 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
–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

1 citing paper in PubMed.

  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

3 authors.

Jason R MillerDepartment of Computer Science and Information Technology; Hood College, Frederick, MD 21701, USA.ORCID https://orcid.org/0000-0002-6912-2925
Weijun YiLane Department of Computer Science and Electrical Engineering; West Virginia University, Morgantown, WV 26506, USA.
Donald A AdjerohLane Department of Computer Science and Electrical Engineering; West Virginia University, Morgantown, WV 26506, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lncATLAS database quantifies the relative cytoplasmic versus nuclear abundance of long non-coding RNAs (lncRNAs) observed in 15 human cell lines. The literature describes several machine learning models trained and evaluated on these and similar datasets. These reports showed moderate performance,

Identifiers

PMID39296930
PMCPMC11409063

What OpenQuestion holds

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LicenceCC BY
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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.