Evidence map›Paper›PMID 26000831›Full record

ArticlePloS one2015

ProteINSIDE to Easily Investigate Proteomics Data from Ruminants: Application to Mine Proteome of Adipose and Muscle Tissues in Bovine Foetuses.

Nicolas Kaspric, Brigitte Picard, Matthieu Reichstadt, Jérémy Tournayre, Muriel Bonnet

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

17 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
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  4. Characterization of the Skeletal Muscle Proteome in Undernourished Old Rats.International journal of molecular sciences · 2022
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  13. Long Non-Coding RNANon-coding RNA · 2019
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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

5 authors at 3 institutions in 1 country.

Nicolas KaspricUMR1213 Herbivores, INRA, Saint-Genès-Champanelle, France; UMR1213 Herbivores, Clermont Université, VetAgro Sup, Clermont-Ferrand, France.
Brigitte PicardUMR1213 Herbivores, INRA, Saint-Genès-Champanelle, France; UMR1213 Herbivores, Clermont Université, VetAgro Sup, Clermont-Ferrand, France.
Matthieu ReichstadtUMR1213 Herbivores, INRA, Saint-Genès-Champanelle, France; UMR1213 Herbivores, Clermont Université, VetAgro Sup, Clermont-Ferrand, France.
Jérémy TournayreUMR1213 Herbivores, INRA, Saint-Genès-Champanelle, France; UMR1213 Herbivores, Clermont Université, VetAgro Sup, Clermont-Ferrand, France.
Muriel BonnetUMR1213 Herbivores, INRA, Saint-Genès-Champanelle, France; UMR1213 Herbivores, Clermont Université, VetAgro Sup, Clermont-Ferrand, France.
Unité Mixte de Recherche sur les Herbivores · FRVetAgro Sup · FRUniversité Clermont Auvergne · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomics experiments are widely acknowledged to produce a huge amount of data to be analysed. The challenge is to extract meaningful biological context for proteins or genes which is currently difficult because of the lack of an integrative workflow that hinders the efficiency and the robustness of data mining performed by biologists working on ruminants. Thus, we designed ProteINSIDE, a free web service (www.proteinside.org) that (I) provides an overview of the biological information stored in public databases or provided by annotations according to the Gene Ontology, (II) predicts proteins that are secreted to search for proteins that mediate signalisation between cells or tissues, and (III) analyses protein-protein interactions to identify proteins contributing to a process or to visualize functional pathways. Using lists of proteins or genes as a unique input, ProteINSIDE is an original all-in-one tool that merges data from these searches to present a fast overview and integrative analysis of genomic and proteomic data from Bovine, Ovine, Caprine, Human, Rat, and Murine species. ProteINSIDE was bench tested with 1000 proteins identifiers from each species by comparison with DAVID, BioMyn, AgBase, PrediSi, and Phobius. Compared to DAVID or BioMyn, identifications and annotations provided by ProteINSIDE were similar from monogastric proteins but more numerous and relevant for ruminants proteins. ProteINSIDE, thanks to SignalP, listed less proteins potentially secreted with a signal peptide than PrediSi and Phobius, in agreement with the low false positive rate of SignalP. In addition ProteINSIDE is the only resource that predicts proteins secreted by cellular processes that do not involve a signal peptide. Lastly, we reported the usefulness of ProteINSIDE to bring new biological hypotheses of research from proteomics data: the biological meaning of the uptake of adiponectin by the foetal muscle and a role for autophagy during ontogenesis of adipose and muscle tissues.

Indexed as

Databases, ProteinAdipose TissueAnimalsCattleHumansMiceMuscle, SkeletalProteomeProteomicsRatsSheepSoftwareProteome

Identifiers

PMID26000831
PMCPMC4441380
OpenAlexW385127522

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.