Evidence map›Paper›PMID 31857603›Full record

ArticleScientific reports2019

OutCyte: a novel tool for predicting unconventional protein secretion.

Linlin Zhao, Gereon Poschmann, Daniel Waldera-Lupa, Nima Rafiee, Markus Kollmann, Kai Stühler

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

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  5. Deep phenotypic profiling uncovers cryptic effects of antifilarial drugs.bioRxiv : the preprint server for biology · 2026
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  7. Endothelial Cell Secretome Alterations Induced by Inflammatory Stress.bioRxiv : the preprint server for biology · 2026
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  8. Aerolysin-like proteins fromFrontiers in fungal biology · 2026
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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

6 authors.

Linlin ZhaoInstitute of Molecular Medicine, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany.
Gereon PoschmannInstitute of Molecular Medicine, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany.
Daniel Waldera-LupaInstitute of Molecular Medicine, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany.
Nima RafieeMathematical Modelling of Biological Systems, Heinrich-Heine-University, Düsseldorf, Germany.
Markus KollmannMathematical Modelling of Biological Systems, Heinrich-Heine-University, Düsseldorf, Germany.
Kai StühlerInstitute of Molecular Medicine, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany. kai.stuehler@hhu.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prediction of protein localization, such as in the extracellular space, from high-throughput data is essential for functional downstream inference. It is well accepted that some secreted proteins go through the classic endoplasmic reticulum-Golgi pathway with the guidance of a signal peptide. However, a large number of proteins have been found to reach the extracellular space by following unconventional secretory pathways. There remains a demand for reliable prediction of unconventional protein secretion (UPS). Here, we present OutCyte, a fast and accurate tool for the prediction of UPS, which for the first time has been built upon experimentally determined UPS proteins. OutCyte mediates the prediction of protein secretion in two steps: first, proteins with N-terminal signals are accurately filtered out; second, proteins without N-terminal signals are classified as UPS or intracellular proteins based on physicochemical features directly generated from their amino acid sequences. We are convinced that OutCyte will play a relevant role in the annotation of experimental data and will therefore contribute to further characterization of the extracellular nature of proteins by considering the commonly neglected UPS proteins.OutCyte has been implemented as a web server at www.outcyte.com.

Indexed as

Secretory PathwayDatasets as TopicHumansMetabolomicsProtein TransportProteomeProteomicsSoftwareProteome

Identifiers

PMID31857603
PMCPMC6923414

What Socratic holds

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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 Socratic graph.