Evidence map›Paper›PMID 36303787›Full record

ArticleFrontiers in bioinformatics2021

Large-Scale Protein Interactions Prediction by Multiple Evidence Analysis Associated With an In-Silico Curation Strategy.

Yasmmin Côrtes Martins, Artur Ziviani, Marisa Fabiana Nicolás, Ana Tereza Ribeiro de Vasconcelos

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Vitiligo Information Resource database v3.NPJ systems biology and applications · 2026
    Article
  2. Regulation ofViruses · 2025
    Review
  3. 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.

Yasmmin Côrtes MartinsBioinformatics Laboratory, National Laboratory of Scientific Computing, Petrópolis, Brazil.
Artur ZivianiData Extreme Lab (DEXL), National Laboratory of Scientific Computing, Petrópolis, Brazil.
Marisa Fabiana NicolásBioinformatics Laboratory, National Laboratory of Scientific Computing, Petrópolis, Brazil.
Ana Tereza Ribeiro de VasconcelosBioinformatics Laboratory, National Laboratory of Scientific Computing, Petrópolis, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Predicting the physical or functional associations through protein-protein interactions (PPIs) represents an integral approach for inferring novel protein functions and discovering new drug targets during repositioning analysis. Recent advances in high-throughput data generation and multi-omics techniques have enabled large-scale PPI predictions, thus promoting several computational methods based on different levels of biological evidence. However, integrating multiple results and strategies to optimize, extract interaction features automatically and scale up the entire PPI prediction process is still challenging. Most procedures do not offer an

Indexed as

in-silico validationlarge-scale predictionPPI predictionprotein-protein interactionscientific workflowtext mining

Identifiers

PMID36303787
PMCPMC9581021

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.