This course is targeted at graduate and medical students, post-docs, clinical fellows, faculty and biomedical industry researchers with either of two backgrounds: training mainly in the biological and biomedical sciences, or training mainly in mathematics, physics, engineering or computer science.
Whatever your background, if you are reading this, you’ve probably had some specific experience—in the classroom, library or laboratory—that led you to wonder whether you could have a more effective and more satisfying research experience by applying methodologies outside of traditional biology, as exemplified in Systems Biology, to problems in cancer.
Systems Biology, which integrates mathematical and computational modeling, network modeling, control theory and information theory, is now being used to provide insight on cancer initiation, progression and response to treatment and promises to identify new and more effective treatments and management strategies.
Many biomedically-trained researchers are unfamiliar, however, with the fundamentals of Systems Biology, which limits their ability to apply this approach to their research. At the same time, non-biomedically-trained researchers who have expertise in the mathematical, computational and engineering sciences are unfamiliar with the fundamentals of Cancer Biology, which limits their ability to apply this knowledge to cancer and to effectively collaborate with cancer biologists.
Our course seeks to bridge these gaps in training and use classroom and wet and dry laboratory experiences to provide a high-level introduction to Systems Biology and its application to cancer relevant problems.