VirHostNet 2.0 · Accueil

What's new in VirHostnet 2.0 (release January 2019) ?

34.760 virus-host and virus-virus manually biocurated protein-protein interactions, including more than 6.000 new interactions since the last January 2018 release
A VirHostNet SOLR PSICQUIC webservice that provides annotations in PSI MI-TAB 2.5 format (download)
The use of UniProtkb/Swiss-Prot TrEMBL (release January 2019) and ReFSeQ (release 92 January 2019) as references
The use of PSICQUIC webservice (January 1st 2019) to download INTACT, MINT, BIOGRID, DIP, Uniprot, MatrixDB, Innatedb, HPIDb, IMEx protein-protein interaction data in PSI-MITAB 2.5 format
Virus' host range annotations provided by Viralzone, Virus-Host DB, and in-house text-mining of genbank are now integrated and used to highlight biologically relevant virus/host ppi
The use of UniProtkb chain feature key - including mature peptides - to annotate protein-protein interactions at a finer scale
The use of MIscore scoring function to measure the quality of each non-redundant interaction based on independant experiments information
Network-based nodes and edges properties (degree, betweeness, ...)
A BLAST webservice to infer novel virus/host ppi from sequences based on the assumption of interology

Follow the trend of virus/host ppi #biocuration here

The Interology web service facilitates the prediction and visualisation of virus-virus and virus-host protein-protein interactions from raw primary protein sequences (in .fasta format).

Predictions rely on the principle of interology assumption, i.e. conservation of homologous protein-protein interactions during evolution. Protein-protein interactions are said to be interologs if the property of interaction between the protein partners and their respective homologous proteins is conserved during the race of virus-host co-evolution. Based on this hypothesis, it is possible to predict virus-virus or virus-host protein-protein interactions between viral strains or within a particular viral species or genus.

A short tutorial on how to use interology inference based on protein sequence homology is availabe here (EBOV predicted interaction network).

Past protein sequences in .fasta format:

OR Load a file of protein sequences from your local disk in .fasta format:

Browse

Matrix:

Gapped:

E-value:

Baltimore group	Family rank	VH network			VV network
Baltimore group	Family rank	ppi	v	h	ppi	v

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