Bioinformatics for Neglected Parasitic Diseases *Course Postponed*

Please note that the Bioinformatics for Neglected Parasitic Diseases course will be postponed to 2018.

Description

This course provides hands-on instruction for researchers in the biological sciences interested in applying bioinformatics tools for research on neglected parasitic diseases.

 

Course Director

Robin Beech, PhD
Associate Professor, Institute of Parasitology, McGill University
Associate Dean, Graduate & Postdoctoral Studies, McGill University

 

 

Content

This will provide hands-on training in the bioinformatics tools that are most often used to investigate parasitic organisms and the resources that are available in the  genome age. These include multiple sequence alignment, phylogeny construction and analysis of gene family expansion and contraction, prediction of protein  structure and function, prediction of ligand binding pockets and in silico drug docking, protein-protein interaction networks and metagenomic analysis. A  description of the major data resources available, including a review of the ParaSite database holding the Helminth Genome Initiative genome data. Biology theory  and analytical techniques will be reviewed in organized presentations each morning, followed by practical use of the tools with concrete examples taken from various nematode and single celled parasitic disease organisms.

 

 

Course Faculty

Reza Salavati, PhD – Institute of Parasitology, McGill University
Jianguo (Jeff) Xia, MD, PhD – Institute of Parasitology and Department of Animal Science, McGill University
James Wasmuth, PhD – Department of Biological Science, University of Calgary

 

 

Target Audience

  • Scientists working in developed and developing countries on parasitic diseases who wish to gain familiarity with bioinformatics tools and protocols
  • Graduate students and postdoctoral fellows interested in this topic
  • Research leaders from developing countries who wish to explore how bioinformatics can be applied in the local context

 

Registration

Maximum of 50 participants.