The Cytokine Signalling Forum (CSF) is an educational website developed under the auspices of the University of Glasgow and is dedicated to the dissemination of the latest development in cytokine signalling. It provides continuing medical education to clinicians around the globe to facilitate greater understanding of the science of cytokines and cytokine signalling, and its implications for clinical practice.
CSF distance learning programmes are free from commercial bias, and feature leading experts sharing their knowledge and experience in the form of video tutorials.
INTERFEROME is an open access database of types I, II and III Interferon regulated genes collected from analysing expression data sets of cells treated with IFNs. This database of interferon regulated genes integrates information from high-throughput experiments with annotation, ontology, orthologue sequences from 37 species, tissue expression patterns and gene regulatory information to enable a detailed investigation of the molecular mechanisms underlying IFN biology. INTERFEROME fulfils a need in infection, immunity, development and cancer research by providing computational tools to assist in identifying interferon signatures in gene lists generated by high-throughput expression technologies, and their potential molecular and biological consequences.
url: www.interferome.org
link to paper:
PMID: 18996892
https://www.ncbi.nlm.nih.gov/pubmed/18996892
There is a lack of bioinformatics resources available for cytokine biologists and INTERFEROME was one of the tools I built to help analyze interferon related microarray/proteomic data sets. Its main function is to identify interferon signatures in high throughput experiments. We’ve already started working on the next version which will have additional functionality.
To expand the capabilities of interferome we need the interferon community to submit high-throughput datasets to be included in INTERFEROME:
1. microarray or proteomic data from IFN treated (TYPE I,II OR III) cells tissues
2. microarray data from IFN treatment in disease situations (viral infections, cancer, multiple sclerosis, lupus etc)
3. STAT or IRF Chip-ChIP or ChIP-Seq datasets
Other issues with which the ICIS membership may be able to help:
1. Help building interferon regulated gene networks – These networks will help identify how these 2000 IRGs we identified mediate interferon biology. If the IFN community used its collective knowledge, building the IRG network isn’t going to be hard. Resources like wikipathways (http://www.wikipathways.org/index.php/WikiPathways) may be useful.
2. Gene nomenclature issues -there are at least 50+ IRGs without a gene name and most IRGs have more than 20 names
Our database is a community resource and there is potential for it’s capabilities to increase with the involvement of the interferon community. We look forward to input from the ICIS membership.
Kind regards,
Shamith
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Shamith Samarajiwa BSc.(Biomedical) (Hons.) PhD.
Computational Biology Group
Department of Oncology
University of Cambridge
Cancer Research UK Cambridge Research Institute
Li Ka Shing Centre
Robinson Way
Cambridge CB2 0RE
England
