Evidence map›Paper›PMID 35891788›Full record

ArticleComputational and structural biotechnology journal2022

Biological interacting units identified in human protein networks reveal tissue-functional diversification and its impact on disease.

Marina L García-Vaquero, Margarida Gama-Carvalho, Francisco R Pinto, Javier De Las Rivas

Open access · goldAbstract read
In one paragraph

Article 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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 at 2 institutions in 2 countries.

Marina L García-VaqueroUniversity of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
Margarida Gama-CarvalhoUniversity of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
Francisco R PintoUniversity of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
Javier De Las RivasCancer Research Center (CiC-IBMCC, CSIC/USAL and IBSAL), Consejo Superior de Investigaciones Científicas (CSIC), University of Salamanca (USAL) and Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca 37007, Spain.
Consejo Superior de Investigaciones Científicas · ESUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions (PPI) play an essential role in the biological processes that occur in the cell. Therefore, the dissection of PPI networks becomes decisive to model functional coordination and predict pathological de-regulation. Cellular networks are dynamic and proteins display varying roles depending on the tissue-interactomic context. Thus, the use of centrality measures in individual proteins fall short to dissect the functional properties of the cell. For this reason, there is a need for more comprehensive, relational, and context-specific ways to analyze the multiple actions of proteins in different cells and identify specific functional assemblies within global biomolecular networks. Under this framework, we define

Indexed as

Biological functionBiU, BioInt unitCO, CORUM complexDEg, Differentially expressed geneDG, Disease geneDisease geneGO-BP, Gene Ontology biological processHK, HousekeepingHousekeeping genePPI networkPPI, Protein-protein interactionProtein moduleSS, Simpson's similarityTE, Tissue enrichedTissue-specific geneTS, Tissue-specificUB, Ubiquitous

Identifiers

PMID35891788
PMCPMC9304429
OpenAlexW4285605236

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.