Tag Archives: Systems Biology

VISIONET on R@CMon (Update)

Back in early 2014, the R@CMon team assisted SBI Australia to deploy the VISIONET (Visualizing Transcriptomic Profiles Integrated with Overlapping Transcription Factor Networks) visualisation web service on the Monash node of the NeCTAR Research Cloud. Since then, VISIONET has been further enhanced to support more complex transcription factor network topologies. To date, VISIONET has been published in two papers.

Nim, H.T., Boyd, S.E., and Rosenthal, N.A. (2014). Systems approaches in integrative cardiac biology: Illustrations from cardiac heterocellular signalling studies. Progress in Biophysics and Molecular Biology 117, 69-77.

Nim, H.T., Furtado, M.E., Costa, M.W., Rosenthal, N.A, Kitano, H., and Boyd, S.E.. (2015). VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery. BMC Bioinformatics.

The R@CMon team will continue supporting SBI Australia with its plan to further develop the VISIONET web service this year.

Interferome on R@CMon

Interferons (IFNs) were identified as antiviral proteins more than 50 years ago. However, their involvement in immunomodulation, cell proliferation, inflammation and other homeostatic process has since been identified. These cytokines are used as therapeutics in many diseases such as chronic viral infections, cancer and multiple sclerosis. These IFNs regulate the transcription of approximately 2000 genes in a IFN subtype, dose, cell type and stimulus dependent manner. 

Interferome Wordle

Interferome Wordle

Interferome is an online database of IFN regulated genes.  The database is a valuable resource for biomedical researchers, being regularly used by scientists from across the world. This database of IFN regulated genes is an attempt at integrating information from high-throughput experiments to gain a detailed understanding of IFN biology. Interferome enables reliable identification of an individual Interferon Regulated Gene (IRG) or IRG signatures from high-throughput data sets (i.e. microarray, proteomic data etc.). It also assists in identifying regulatory elements, chromosomal location and tissue expression of IRGs in humans and mice.

Interferome Database Statistics

Interferome Database Statistics

The R@CMon team assisted Prof. Paul Hertzog and the Centre of Innate Immunity & Infectious Diseases at MIMR-PHI in migrating versions 1.0 and 2.0 of the Interferome online database into the NeCTAR Research Cloud. Interferome Version 2.0 has quantitative data, more detailed annotation and search capabilities and can be queried for one gene or thousands as in a gene list from a microarray experiment. To ensure availability of data and assist researchers with hypothesis generation and novel biological discoveries, the Interferome database is backed by VicNode Collection 2014R9.06. More information about Interferome is available on the help page.


VISIONET (Visualizing Transcriptomic Profiles Integrated with Overlapping Transcription Factor Networks) is a visualisation web service for cellular regulatory network studies. It’s been developed as a tool for creating human-readable visualisations of transcription factor networks from user’s microarray and ChiP-seq input data. VISIONET’s node-filtering feature provides a more human-readable large networks visualisation compared to CellDesigner and Cytoscape


Gata4-Tbx20 transcription factor network.

R@CMon helped SBI Australia in porting the VISIONET web service into the NeCTAR Research Cloud, enabling rapid development and customisation. VISIONET’s .NET-based framework is now running on a Windows Server 2012 instance inside R@CMon, and it’s now using persistent storage (Volumes) for storing large generated network visualisations. VISIONET is now publicly available to biologists, and user traffic is expected to grow in the near future.

Garuda/Flint K3 @ NeCTAR Research Cloud

We’re currently working on deploying the Garuda/Flint K3 system in the NeCTAR Research Cloud.

The Garuda platform provides fundamental technology to link software and knowledge in systems biology in a coherent manner.

Flint K3 is an online simulation platform that receives PHML and SBML models from PhysioDesigner, CellDesigner and other applications.

More about the Systems Biology Institute can be found on their website.