Welcome to the Bioinformatics and Computational Genomics Laboratory of
The Bioinformatics and Computational Genomics Laboratory is part of the Princess Margaret Cancer Centre – University Health Network, located in the heart of the Toronto Discovery District. Our research focuses on the development of novel computational approaches to best characterize carcinogenesis and drug mechanisms of action from high-throughput genomic data. We have strong expertise in prognostic and predictive biomarkers identification and drug repurposing.
The Princess Margaret Cancer Centre is a teaching hospital within the University Health Network and affiliated with the University of Toronto. It has the largest cancer research program in Canada. This rich working environment provides ample opportunities for collaboration and scientific exchange with a large community of clinical, genomics, computational biology, and machine learning groups at the University of Toronto and associated institutions, such as The Hospital for Sick Children and the Donnelly Centre.
- Dr. Zhaleh Safikhani received “2018 Vector Best Poster Award” for presenting the poster at 2018 Toronto Machine Learning Summit.
- Dr. Zhaleh Safikhani gives a talk titled Drug combination discovery using single-cell sequencing at Biological Data Science 2018, CSHL, NY, USA. Here is a link to the presentation: https://docs.google.com/presentation/d/1y1KXw6kOmiPJtCybsqRVkDsh0kfhCf1zXn6XbaWtQAM/edit?usp=sharing The video of the talk is also available here: http://theleadingstrand.cshl.edu/meeting/media
- Seyed Ali Madani Tonekaboni preseneted a poster titled Clusters of Cis-regulatory Element, Topologically Associated Domain, CTCF, Cohesin Complex at Canadian Epigenetics, Environment and Health Research Consortium (CEEHRC), October 2018.
- Dr. Zhaleh Safikhani gives a talk titled Tackling pharmacogenomics problems using computational biology at BioC 2018, Toronto, Canada.
More stories can be read on the News page.
There are currently positions available in the lab for Software Developers, Postdoctoral Fellows, Graduate and Undergraduate Students in Cancer Computational Biology. Our research focuses on the development of novel computational approaches to best characterize carcinogenesis, drug mechanisms of action and therapeutic potential from high-throughput genomic data. Learn more on the Positions page.