Evidence map›Paper›PMID 39781514›Full record

ArticleNAR genomics and bioinformatics2025

PSAURON: a tool for assessing protein annotation across a broad range of species.

Markus J Sommer, Aleksey V Zimin, Steven L Salzberg

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Markus J SommerDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0003-3414-1875
Aleksey V ZiminDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Steven L SalzbergDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0002-8859-7432

Funding

Computational Methods for Microbial and Microbiome Sequence AnalysisR35GM130151 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Steven L. Salzberg · 2019 to 2026
$2.9M
NIGMS NIH HHS R35 GM130151
6 · The paper itself

Abstract

Evaluating the accuracy of protein-coding sequences in genome annotations is a challenging problem for which there is no broadly applicable solution. In this manuscript, we introduce PSAURON (Protein Sequence Assessment Using a Reference ORF Network), a novel software tool developed to help assess the quality of protein-coding gene annotations. Utilizing a machine learning model trained on a diverse dataset from over 1000 plant and animal genomes, PSAURON assigns a score to coding DNA or protein sequence that reflects the likelihood that the sequence is a genuine protein-coding region. PSAURON scores can be used for genome-wide protein annotation assessment as well as the rapid identification of potentially spurious annotated proteins. Validation against established benchmarks demonstrates PSAURON's effectiveness and correlation with recognized measures of protein quality, highlighting its potential use as a widely applicable method to evaluate precision in gene annotation. PSAURON is open source and freely available at https://github.com/salzberg-lab/PSAURON.

Indexed as

Molecular Sequence AnnotationSoftwareAnimalsMachine LearningOpen Reading Frames

Identifiers

PMID39781514
PMCPMC11704789

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.