Evidence map›Paper›PMID 35832626›Full record

ReviewComputational and structural biotechnology journal2022

Construction and contextualization approaches for protein-protein interaction networks.

Apurva Badkas, Sébastien De Landtsheer, Thomas Sauter

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Computational and structural biotechnology journal · 2025
    Article
  5. Heterogeneous network approaches to protein pathway prediction.Computational and structural biotechnology journal · 2024
    Review
  6. Article
  7. 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

3 authors.

Apurva BadkasDepartment of Life Sciences and Medicine, University of Luxembourg, Belval Campus, 2, avenue de l'Université, L-4365 Esch-sur-Alzette, Luxembourg.
Sébastien De LandtsheerDepartment of Life Sciences and Medicine, University of Luxembourg, Belval Campus, 2, avenue de l'Université, L-4365 Esch-sur-Alzette, Luxembourg.
Thomas SauterDepartment of Life Sciences and Medicine, University of Luxembourg, Belval Campus, 2, avenue de l'Université, L-4365 Esch-sur-Alzette, Luxembourg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interaction network (PPIN) analysis is a widely used method to study the contextual role of proteins of interest, to predict novel disease genes, disease or functional modules, and to identify novel drug targets. PPIN-based analysis uses both generic and context-specific networks. Multiple contextualization methodologies have been described, such as shortest-path algorithms, neighborhood-based methods, and diffusion/propagation algorithms. This review discusses these methods, provides intuitive representations of PPIN contextualization, and also examines how the quality of such context-specific networks could be improved by considering additional sources of evidence. As a heuristic, we observe that tasks such as identifying disease genes, drug targets, and protein complexes should consider local neighborhoods, while uncovering disease mechanisms and discovering disease-pathways would gain from diffusion-based construction.

Indexed as

Context-specific networkDiffusionNeighborhoodProtein-protein interaction network

Identifiers

PMID35832626
PMCPMC9251778

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.