Senior Program Manager
Dr. Michelle Brazas
The Computational Biology Program is the scientific engine of research and analytics at OICR. The program’s investigators lead local and international cancer genomics research studies and programs. In many cases, the program’s teams develop new algorithms, software, visualization tools and other necessary components to interrogate and interpret the large and complex datasets. Our resources and expertise are shared with the Ontario and the international cancer research community, with the goal of supporting the acceleration of cancer research.
Our mission is to advance the knowledge and treatment of cancer through computational biology.
Our research objectives are to:
- Gain new and deeper understanding of cancer biology through the application of computational and data-intensive techniques;
- Train the next generation of computational biologists to work on cancer-related problems;
- Foster efficiency, communication and collaboration within and among Computational Biology and Genome Informatics, OICR and the wider community.
Principal investigators and senior scientists in the Computational Biology Program have a broad set of research interests and expertise, ranging from open research and reproducibility, to algorithm development for long-read sequences, pipelines for sequencing and analysis, biomarker discovery, viral detection, and population-based genomics approaches to cancer, as well as pathway and network analysis. While our research activities and expertise focus on cancer, they also have broader application in genomic research.
The Computational Biology Program is involved in a wide variety of research projects. We play both leadership, and collaborative, scientific roles in many cancer research projects, with a strong mandate to output to the scientific community open-source, open-access data, tools and resources.
Projects under the Computational Biology Program include:
(CPC-GENE), a project aimed at understanding the prostate cancer genome to better predict treatment failure for intermediate risk prostate cancers.
A pan-Canada research project to rapidly develop novel diagnostic markers for early prostate cancer.
Which supports large scale genomics projects on population-wide and clinical cohorts, and provides analytical and bioinformatics support through access to the software and analytic systems needed to collect and harmonize diverse health and lifestyle data, analyze it and electronically publish the results. Researchers can request access and services for their project needs.
Which provides global coordination of benchmarking algorithms for analyzing cancer genomes.
The Ontario Health Study is a provincial cohort built to understand the development of cancer and chronic diseases in cancer.
The Canadian Partnership for Tomorrow Project is a national cohort built to understand the development of cancer and chronic diseases in cancer.
An online biological database about the biology and genome of the nematode model organism Caenorhabditis elegans.
The Generic Model Organism Database project is a collection of open source software tools for managing, visualising, storing, and disseminating genetic and genomic data.