Interferome statistics

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Citations per year

Number of citations per year for the bioinformatics software tool Interferome
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Tool usage distribution map

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Protocols

Interferome specifications

Information


Unique identifier OMICS_03056
Name Interferome
Restrictions to use None
Database management system MySQL
Community driven No
Data access Browse
User data submission Allowed
Version 2.01
Maintained Yes
Wikipedia https://en.wikipedia.org/wiki/Interferome

Maintainer


  • person_outline Paul Hertzog

Publications for Interferome

Interferome citations

 (24)
library_books

A direct link between MITF, innate immunity, and hair graying

2018
PLoS Biol
PMCID: 5933715
PMID: 29723194
DOI: 10.1371/journal.pbio.2003648

[…] he 411 genes with a greater than 1.5-fold up-regulation in Mitfmi-vga9/+ cells, at least 55 are known for their involvement in type I innate immune signaling (DAVID Functional Annotation Tool [,] and interferome.org []). These include cytoplasmic pattern recognition receptors (PRRs; Ddx58, Ifih1), transcriptional regulators (Irf7, Stat1), and IFN-stimulated genes (ISGs) that execute the antiviral […]

library_books

Type I interferon signaling attenuates regulatory T cell function in viral infection and in the tumor microenvironment

2018
PLoS Pathog
PMCID: 5929570
PMID: 29672594
DOI: 10.1371/journal.ppat.1006985

[…] ially expressed (249 genes were down, and 337 genes were up) in IFNARfl/fl x Foxp3YFP-Cre mice (fold change 1.5 and above, adjusted P < 0.05) (). Among the 586 genes, 174 genes were identified in the interferome database [] (interferome.its.monash.edu.au) as IFN-signaling related (fold change 1.5 and above, adjusted P < 0.05) (), and were excluded from further analysis. We elected to exclude IFNAR […]

call_split

Impact of Interferon α Receptor 1 Promoter Polymorphisms on the Transcriptome of the Hepatitis B Virus Associated Hepatocellular Carcinoma

2018
Front Immunol
PMCID: 5911724
PMID: 29713327
DOI: 10.3389/fimmu.2018.00777
call_split See protocol

[…] scriptome reference (v.GRCh38.rel79) and to calculate the transcripts abundances. We analyzed the impact of the IFNARPPs on the transcriptional landscape of the interferon-associated genes using the “Interferome” database () on a subset our whole-transcriptome results. We used Sleuth () and R-base functions to interpret and visualize the RNA-seq analysis results. We performed Gene Ontology (GO) an […]

library_books

Fundamental properties of the mammalian innate immune system revealed by multispecies comparison of type I interferon responses

2017
PLoS Biol
PMCID: 5747502
PMID: 29253856
DOI: 10.1371/journal.pbio.2004086

[…] Clusters comprising one-to-one orthologs present in the interferome of each species were extracted and filtered to check for the presence of a gene in species X matching a human Ensembl ID. The human Ensembl ID was then used to query BioMart to extract the […]

library_books

Comparative proteomics as a tool for identifying specific alterations within interferon response pathways in human glioblastoma multiforme cells

2017
Oncotarget
PMCID: 5788599
PMID: 29416731
DOI: 10.18632/oncotarget.22751

[…] ontology analysis of differentially expressed proteins satisfying criteria fdrBH < 0.05, FC ≤ 0.4 and ≥ 2.5 was performed. The proteins derived using statistical workflows A and C were analyzed using INTERFEROME, STRING and GOrilla databases [–]. The results are shown in and for workflows A and C, respectively.As shown in , all the applied tools for both A-172 and DBTRG-05MG cell lines reveal th […]

call_split

Mef2C restrains microglial inflammatory response and is lost in brain ageing in an IFN I dependent manner

2017
Nat Commun
PMCID: 5620041
PMID: 28959042
DOI: 10.1038/s41467-017-00769-0
call_split See protocol

[…] ncreased or decreased genes (as a target set) and a complete gene list (as a background set) were imported. Venn diagram of IFN type I (α and β), II (IFN-γ), and III-dependent genes was created using Interferome v. 2.01 (http://www.interferome.org/interferome/search/showSearch.jspx) with default parameters. Heat-map was prepared using GENE-E (http://www.broadinstitute.org/cancer/software/GENE-E/). […]


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Interferome institution(s)
Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, VIC, Australia; ARC Centre of Excellence for Structural and Functional Microbial Genomics, Monash University, Clayton, VIC, Australia; Monash e-Research, Monash University, Clayton, VIC, Australia; Universite Paris Descartes, Paris, France
Interferome funding source(s)
Supported by The Australian National Health and Medical Research Council; the Australian National Data Service; the Australian Research Council’s Centre of Excellence in Structural and Functional Microbial Genomics and the Universite Paris Descartes; and the Victorian Government’s Operational Infrastructure Support Program.

Interferome review

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isaac

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Dataset
The Interferome service has a great website with extensive databases that can be interrogated easily using the online search query inputs. The site is a must-see for any researchers in the field of immunity, particularly those working with interferon responses.