Department of Biochemistry
Using computers to understand the biology of cancer
McIntyre Medical Sciences Building
3655 promenade Sir-William-Osler
Office: Room 805B; Lab: 805
Montreal, Quebec H3G 1Y6
Tel: 514-398-8526; Lab: TBA
Email: uri [dot] david [dot] akavia [at] mcgill [dot] ca
2009 – PhD, Tel-Aviv University, Sackler School of Medicine
Positions open for students and post-doctoral fellows, uri [dot] akavia [at] mcgill [dot] ca (email) CV and transcript. The ideal student would have a strong background in both programming and biology. Students with a strong background in one field and some knowledge in the other will also be considered.
My lab devises and applies algorithms in computational biology to cancer, combining them with experimental approaches to systematically identify viable drug targets in the context of cancer therapeutics. The combination of these approaches will provide a fundamental understanding of oncogenesis, while focusing on clinically relevant questions. Our goal is to reduce the genome-wide datasets available for cancer models and patients to a small series of experimentally testable questions.
We are especially interested in:
- Identifying new genes contributing to cancer progression and clinical phenotype, including their targets
- Building the network of relationships between drivers, and between drivers and the biological pathways they control
- Applying computational approaches to personalized medicine, and
- Translating results from bench to bedside, to have as much clinical impact as possible
I am currently working on Brain Tumor (Glioblastoma), Breast Cancer and Diffuse Large B-Cell Lymphoma (DLBCL). All of these cancers contain interesting challenges, both computational and biological.
Publications (complete list) - Uri David Akavia