Tutorial details

Date: Sunday September 4, 2016
Time: 13:30 – 17:00 (half day tutorial)
Venue: World Forum, room: Asia

Tutorial website

Tutors

• Laura I. Furlong, Miguel Servet Researcher and Associate Professor at the University Pompeu Fabra and Head of the Integrative Biomedical Informatics Group of the Research Programme on Biomedical Informatics, GRIB (IMIM-UPF) at Barcelona (Spain)
• Janet Piñero, post-doctoral researcher at the Integrative Biomedical Informatics Group of the Research Programme on Biomedical Informatics, GRIB (IMIM-UPF) at Barcelona (Spain)

Summary

Recent technological breakthroughs have produced an unprecedented increase in the amount of data on the genetic determinants of diseases. To unveil the molecular mechanisms that underlie diseases and to support drug discovery projects, it is necessary to place these data in the context of the current biomedical knowledge. Despite the large volume of information available, its analysis and interpretation are hindered because it is annotated using different criteria and vocabularies and fragmented across different resources. Furthermore, a large fraction of data on diseases is only available as free text in biomedical publications. To overcome these difficulties we have developed DisGeNET (Piñero et al, 2015), a discovery platform that contains information on human diseases and their genes.

In this tutorial we will provide an overview of the main features of DisGeNET, and then introduce the suite of tools that the platform offers to support translational research.  The tutorial includes a hands-on session organized around case studies that will illustrate how to use these tools.

The case studies that we will tackle include:

1. What is the profile of diseases associated to a gene of interest?
2. What are the genes associated to a particular disease?
3. What are the evidences linking a disease to its associated genes?
4. What are the genes shared by comorbid diseases?
5. What are the genetic variants associated to a particular disease?
6. What proteins associated to a particular disease are also targets of drugs?

The DisGeNET tools that we will use in these case studies are:

1. The Web interface, supporting user-friendly data exploration and downloading,
2. The SPARQL endpoint and Faceted Browser to show how the information contained in DisGeNET can be navigated, integrated and analyzed in the current biomedical knowledge using Semantic Web technologies,
3. The DisGeNET Cytoscape app, to analyze the gene-disease associations from a systems biology perspective,
4. The disgenet2r R package, which includes a variety of functions to explore DisGeNET information using the statistical analysis and visualization capabilities of the R environment and Bioconductor packages.

Target audience

The tutorial is aimed at a variety of audiences: bioinformaticians, systems biology users, biologists, and healthcare practitioners.

Schedule, requirements and materials

For detailed schedule and requirements, please visit the tutorial website!

Tutorial website