Workshop details

Date: Saturday September 3, 2016
Time: 9:00 – 17:00
Venue: World Forum, room: South America

Workshop website

Organisers

• Prof. Igor Jurisica, Tier I Canada Research Chair in Integrative Cancer Informatics, University of Toronto, Canada
• Prof. Natasa Przulj, Professor of Biomedical Data Science, Department of Computer Science, University College London, UK
• Prof. Tijana Milenkovic, Assistant Professor, Department of Computer Science, University of Notre Dame, USA

Summary

Interaction networks provide the link between data sources, genotype and phenotype, structure and function of the cell, tissue and organism. In particular, networks are necessary for a comprehensive understanding of the information flow in the cell, the coordination of cellular processes and their condition-specific nature. As such, integrated network-based analyses of clinical and molecular data will become increasingly important for enabling stratified and individualized medicine (precision medicine). Coping with false positives and false negatives, as well as scalability of algorithms and tools is paramount. Using proper data sources, understanding limitations and correctly interpreting results are essential. Even though comprehensive data generation, analysis and visualization are at their beginnings, it has already become clear that analysis of condition-specific networks, their evolution and dynamics will be essential in all aspects of precision medicine. This workshop consists of invited and contributed talks on these timely issues, by bringing together scientists at all career stages from academia and industry with expertise in computational, machine learning, network-based, or mathematical modeling and analyses of large-scale biomedical network data, as well as experimentalists who apply computational network methods to diverse biomedical problems, including disease, drug repositioning, aging, cancer and other disease progression, pharmacogenomics, personalized therapeutics, and healthcare.

Target audience

The workshop aims to bring together scientists at all stages of their career from academia and industry with expertise in computational, machine learning, network-based, or mathematical modeling and analyses of large-scale biomedical network data, as well experimentalists interested in applying computational network methods to diverse biomedical problems, including (but not limited to) disease, drug repositioning, aging, cancer and other disease progression, pharmacogenomics, personalized therapeutics, and healthcare.