Evidence map›Paper›PMID 35531299›Full record

ReviewFrontiers in microbiology2022

The Intricacy of the Viral-Human Protein Interaction Networks: Resources, Data, and Analyses.

Deeya Saha, Marta Iannuccelli, Christine Brun, Andreas Zanzoni, Luana Licata

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 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. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Bioinformatics approaches for unveiling virus-host interactions.Computational and structural biotechnology journal · 2023
    Review
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.

Deeya SahaAix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France.
Marta IannuccelliDepartment of Biology, University of Rome Tor Vergata, Rome, Italy.
Christine BrunAix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France.
Andreas ZanzoniAix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France.
Luana LicataDepartment of Biology, University of Rome Tor Vergata, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral infections are one of the major causes of human diseases that cause yearly millions of deaths and seriously threaten global health, as we have experienced with the COVID-19 pandemic. Numerous approaches have been adopted to understand viral diseases and develop pharmacological treatments. Among them, the study of virus-host protein-protein interactions is a powerful strategy to comprehend the molecular mechanisms employed by the virus to infect the host cells and to interact with their components. Experimental protein-protein interactions described in the scientific literature have been systematically captured into several molecular interaction databases. These data are organized in structured formats and can be easily downloaded by users to perform further bioinformatic and network studies. Network analysis of available virus-host interactomes allow us to understand how the host interactome is perturbed upon viral infection and what are the key host proteins targeted by the virus and the main cellular pathways that are subverted. In this review, we give an overview of publicly available viral-human protein-protein interactions resources and the community standards, curation rules and adopted ontologies. A description of the main virus-human interactome available is provided, together with the main network analyses that have been performed. We finally discuss the main limitations and future challenges to assess the quality and reliability of protein-protein interaction datasets and resources.

Indexed as

emerging virusesmolecular interaction data standardsprotein-protein interactionsSARS-CoV-2virus-host protein-protein interaction databasesvirus-human interactomes

Identifiers

PMID35531299
PMCPMC9069133

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.