Evidence map›Paper›PMID 32575886›Full record

ArticleGenes2020

Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms.

Ekaterina Poverennaya, Olga Kiseleva, Anastasia Romanova, Mikhail Pyatnitskiy

Abstract read
In one paragraph

Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. An ascomycete H4 variant with an unknown function.Royal Society open science · 2024
    Article
  4. Article
  5. Article
  6. Review
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.

Ekaterina PoverennayaInstitute of Biomedical Chemistry, 119121 Moscow, Russia.ORCID 0000-0003-1838-3604
Olga KiselevaInstitute of Biomedical Chemistry, 119121 Moscow, Russia.
Anastasia RomanovaInstitute of Biomedical Chemistry, 119121 Moscow, Russia.
Mikhail PyatnitskiyInstitute of Biomedical Chemistry, 119121 Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite tremendous efforts in genomics, transcriptomics, and proteomics communities, there is still no comprehensive data about the exact number of protein-coding genes, translated proteoforms, and their function. In addition, by now, we lack functional annotation for 1193 genes, where expression was confirmed at the proteomic level (uPE1 proteins). We re-analyzed results of AP-MS experiments from the BioPlex 2.0 database to predict functions of uPE1 proteins and their splice forms. By building a protein-protein interaction network for 12 ths. identified proteins encoded by 11 ths. genes, we were able to predict Gene Ontology categories for a total of 387 uPE1 genes. We predicted different functions for canonical and alternatively spliced forms for four uPE1 genes. In total, functional differences were revealed for 62 proteoforms encoded by 31 genes. Based on these results, it can be carefully concluded that the dynamics and versatility of the interactome is ensured by changing the dominant splice form. Overall, we propose that analysis of large-scale AP-MS experiments performed for various cell lines and under various conditions is a key to understanding the full potential of genes role in cellular processes.

Indexed as

Molecular Sequence AnnotationProteomicsAlternative SplicingComputational BiologyDatabases, ProteinGene OntologyHumansProtein Interaction MapsProteomeProteomeAP-MSBioPlexfunction annotationGene Ontologyhuman interactomeprotein coding genesprotein–protein interactionproteoformsplice formuPE1 proteins

Identifiers

PMID32575886
PMCPMC7350264

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.