Evidence map›Paper›PMID 42465455›Full record

ArticlebioRxiv : the preprint server for biology2026

ProtPen combines sequence- and structure-based approaches to facilitate protein function predictions on a proteome-wide scale.

Diya Mathai, Stefan Schulze

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Diya MathaiGosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA.ORCID 0009-0009-3447-980X
Stefan SchulzeGosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA.ORCID 0000-0002-4771-7987

Funding

Elucidating the roles of protein glycosylation in prokaryotes through functional glycoproteomicsR16GM159790 · NIGMS · ROCHESTER INSTITUTE OF TECHNOLOGY · PI Stefan Schulze · 2025 to 2026
$373k
NIGMS NIH HHS R16 GM159790
6 · The paper itself

Abstract

Proteins of unknown function represent a significant gap in our understanding of biological processes, encompassing large portions of the proteomes of many organisms, especially prokaryotes. Addressing this gap is critical to understanding the biology and pathogenicity of such organisms. We introduce ProtPen, an open-source pipeline that facilitates protein function prediction by combining eggNOG-mapper for sequence-based annotation with Foldseek for rapid structural similarity searches using AlphaFold-predicted protein structures. Annotation results from both tools are merged and enriched with UniProt metadata to produce a comprehensive output suitable for downstream analysis. The pipeline requires only a FASTA input file with UniProt identifiers, and is designed to analyze datasets on the scale of whole proteomes. Benchmarking on a curated dataset of well-characterized

Indexed as

microbiologyorthologyprotein function annotationprotein structureproteomics

Identifiers

PMID42465455
PMCPMC13371080

What OpenQuestion holds

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LicenceCC BY-ND
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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.