Jasmin Fisher

Biography

Jasmin Fisher is a Senior Researcher at Microsoft Research Cambridge in the Programming Principles & Tools group. She is also an Associate Professor of Systems Biology in the Department of Biochemistry at the University of Cambridge. She is a member of the Cancer Research UK Cambridge Centre, Cambridge Systems Biology Centre and the Cambridge Stem Cell Institute, and in 2016 she was elected Fellow of Trinity Hall, Cambridge.   Jasmin received her Ph.D. in Neuroimmunology from the Weizmann Institute of Science in 2003. She then started her work on the application of formal methods to biology as a postdoctoral fellow in the Department of Computer Science at the Weizmann Institute, and then continued to work on the development of novel formalisms and tools that are specifically-tailored for modelling biological processes in the School of Computer Science at the EPFL in Switzerland. In 2007, Jasmin joined the Microsoft Research Lab in Cambridge. In 2009, she was also appointed a Research Group Leader in the University of Cambridge.   Jasmin has devoted her career to develop methods for Executable Biology; her work has inspired the design of many new biological studies. She is a pioneer in using formal verification methods to analyse mechanistic models of cellular processes and disease. Her research group focuses on cutting-edge technologies for modelling molecular mechanisms of cancer and the development of novel drug therapies. 

Research Interest

 Our research focuses on the design and analysis of executable computer algorithms describing biological phenomena, in particular cancer biology. We call this approach Executable Biology. These kinds of models hold great promise for new discoveries in a wide variety of biological systems. Once an executable model has been built of a particular system, it can be used to get a global dynamic picture of how the system responds to various perturbations. In addition, preliminary studies can be quickly performed using executable models, saving valuable laboratory time and resources for only the most promising avenues.