Evidence map›Paper›PMID 28365718›Full record

ArticleDatabase : the journal of biological databases and curation2017

VerSeDa: vertebrate secretome database.

Ana R Cortazar, José A Oguiza, Ana M Aransay, José L Lavín

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Secretome-Based Screening in Target Discovery.SLAS discovery : advancing life sciences R & D · 2020
    Review
  12. Gliome database: a comprehensive web-based tool to access and analyze glia secretome data.Database : the journal of biological databases and curation · 2020
    Article
  13. Article
  14. Article
  15. Article
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.

Ana R CortazarGenome Analysis Platform, CIC bioGUNE & CIBERehd, Bizkaia Technology Park, 48160 Derio, Spain.
José A OguizaGenetics and Microbiology Research Group, Department of Agrarian Production, Public University of Navarre, 31006 Pamplona, Spain.
Ana M AransayGenome Analysis Platform, CIC bioGUNE & CIBERehd, Bizkaia Technology Park, 48160 Derio, Spain.
José L LavínGenome Analysis Platform, CIC bioGUNE & CIBERehd, Bizkaia Technology Park, 48160 Derio, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on the current tools, de novo secretome (full set of proteins secreted by an organism) prediction is a time consuming bioinformatic task that requires a multifactorial analysis in order to obtain reliable in silico predictions. Hence, to accelerate this process and offer researchers a reliable repository where secretome information can be obtained for vertebrates and model organisms, we have developed VerSeDa (Vertebrate Secretome Database). This freely available database stores information about proteins that are predicted to be secreted through the classical and non-classical mechanisms, for the wide range of vertebrate species deposited at the NCBI, UCSC and ENSEMBL sites. To our knowledge, VerSeDa is the only state-of-the-art database designed to store secretome data from multiple vertebrate genomes, thus, saving an important amount of time spent in the prediction of protein features that can be retrieved from this repository directly. Database URL: VerSeDa is freely available at http://genomics.cicbiogune.es/VerSeDa/index.php.

Indexed as

Databases, ProteinGenomeAnimalsProteomeVertebratesProteome

Identifiers

PMID28365718
PMCPMC5467544

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.