Evidence map›Paper›PMID 21255393›Full record

ArticleBMC systems biology2011

When the human viral infectome and diseasome networks collide: towards a systems biology platform for the aetiology of human diseases.

Vincent Navratil, Benoit de Chassey, Chantal Rabourdin Combe, Vincent Lotteau

Abstract read
In one paragraph

Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
–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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Viruses traverse the human proteome through peptide interfaces that can be biomimetically leveraged for drug discovery.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Review
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  10. Analyzing host-viral interactome of SARS-CoV-2 for identifying vulnerable host proteins during COVID-19 pathogenesis.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021
    Article
  11. Article
  12. Article
  13. Protein-protein interactions of human viruses.Seminars in cell & developmental biology · 2020
    Review
  14. Article
  15. Defining Pharmacological Targets by Analysis of Virus-Host Protein Interactions.Advances in protein chemistry and structural biology · 2018
    Review
  16. Article
  17. Article
  18. TheFrontiers in aging neuroscience · 2017
    Article
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  20. 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.

Vincent NavratilUniversité de Lyon, IFR128 BioSciences Lyon-Gerland, Lyon 69007, France. navratil@prabi.fr
Benoit de Chassey
Chantal Rabourdin Combe
Vincent Lotteau

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComprehensive understanding of molecular mechanisms underlying viral infection is a major challenge towards the discovery of new antiviral drugs and susceptibility factors of human diseases. New advances in the field are expected from systems-level modelling and integration of the incessant torrent of high-throughput "-omics" data.

resultsHere, we describe the Human Infectome protein interaction Network, a novel systems virology model of a virtual virus-infected human cell concerning 110 viruses. This in silico model was applied to comprehensively explore the molecular relationships between viruses and their associated diseases. This was done by merging virus-host and host-host physical protein-protein interactomes with the set of genes essential for viral replication and involved in human genetic diseases. This systems-level approach provides strong evidence that viral proteomes target a wide range of functional and inter-connected modules of proteins as well as highly central and bridging proteins within the human interactome. The high centrality of targeted proteins was correlated to their essentiality for viruses' lifecycle, using functional genomic RNAi data. A stealth-attack of viruses on proteins bridging cellular functions was demonstrated by simulation of cellular network perturbations, a property that could be essential in the molecular aetiology of some human diseases. Networking the Human Infectome and Diseasome unravels the connectivity of viruses to a wide range of diseases and profiled molecular basis of Hepatitis C Virus-induced diseases as well as 38 new candidate genetic predisposition factors involved in type 1 diabetes mellitus.

conclusionsThe Human Infectome and Diseasome Networks described here provide a unique gateway towards the comprehensive modelling and analysis of the systems level properties associated to viral infection as well as candidate genes potentially involved in the molecular aetiology of human diseases.

Indexed as

Metabolic Networks and PathwaysCommunicable DiseasesDiabetes Mellitus, Type 1HepacivirusHost-Parasite InteractionsHumansMolecular Sequence AnnotationProteomeSystems BiologyProteome

Identifiers

PMID21255393
PMCPMC3037315

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LicenceCC BY
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Registered trials

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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.