Dr. Joseph Geraci, Ph.D
MaRS\TMDT Signaling Biology Lab
and Princess Margaret Hospital
I can be reached at:
jgeraci at math dot toronto dot edu OR jgeraci at uhnresearch dot ca
Dr. Joseph Geraci, Ph.DMaRS\TMDT Signaling Biology Lab and Princess Margaret Hospital I can be reached at:
jgeraci at math dot toronto dot edu OR jgeraci at uhnresearch dot ca
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Background
When I began my university education I studied Neuroscience and philosophy. I later concentrated on Physics and eventually moved to pure mathematics. I completed an MSc. with I.M. Sigal's group at the University of Toronto where I studied non-linear partial differntial equations and mathematical physics and concentrated on the study of solitons. After completing my Master's degree I entered the Ph.D. program in Applied Mathematics and continued my study of non-linear PDE's but eventually decided to make a move into Quantum Computation. I spent two years with Daniel Lidar's group at the University of Southern California (Go Trojans!) where I discovered new connections between quantum information and statistical physics. I have since completed my doctorate in applied mathematics from the University of Toronto. I continue to stay involved with the quantum community and continue my research on my spare time. I am excited to apply a good dose of creativity, computer science and mathematics to aid the medical community in their fight against cancer.
Current Research
As a member of the Ontario Cancer Institute, I am interested in any way that unexplored areas of mathematics could bridge gaps in our biological understanding of the underlying causes/functioning of cancer. I am currently looking at how a dynamical systems approach could aid in our understanding of how single nucleotide polymorphisms (SNPs) correlate with disease, specifically head and neck cancer and cystic fibrosis. In addition, I am interested in developing in-silico methods for performing preliminary drug trials, specifically for lung and breast cancer, in addition to the discovery of new drug targets. I have recently completed a paper where we used graph theoretical techniques to extend the EGFR pathway with members that correspons to genes that have functional SNPs. An ongoing project is an effort to develop toy models that explore the correspondence between amino acid sequences and the three dimensional structure of proteins. I am also developing an archive of mathematical problems whose solutions will have a significant impact in medicine.
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