Evidence map›Paper›PMID 27198619›Full record

ArticleScientific reports2016

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins.

Raphaël Champeimont, Elodie Laine, Shuang-Wei Hu, Francois Penin, Alessandra Carbone

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

18 citing papers in PubMed, 33 citations in OpenAlex.

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  4. Activation of the CaViruses · 2022
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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 at 2 institutions in 1 country.

Raphaël ChampeimontSorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, 15 rue de l'Ecole de Médecine, 75006 Paris, France.
Elodie LaineSorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, 15 rue de l'Ecole de Médecine, 75006 Paris, France.
Shuang-Wei HuSorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, 15 rue de l'Ecole de Médecine, 75006 Paris, France.
Francois PeninCNRS, UMR5086, Bases Moléculaires et Structurales des Systèmes Infectieux, Institut de Biologie et Chimie des Protéines, 7 Passage du Vercors, Cedex 07, F-69367 Lyon, France.
Alessandra CarboneSorbonne Universités, UPMC-Univ P6, CNRS, Laboratoire de Biologie Computationnelle et Quantitative - UMR 7238, 15 rue de l'Ecole de Médecine, 75006 Paris, France.
Centre National de la Recherche Scientifique · FRUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

Indexed as

Base SequenceBinding SitesComputational BiologyEvolution, MolecularGenome, ViralGenotypeHepacivirusModels, MolecularProtein BindingProtein Interaction MapsViral ProteinsViral Proteins

Identifiers

PMID27198619
PMCPMC4873791
OpenAlexW2402425474

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.