Early Detection and Prevention Division
Center for Cancer Prevention and Early Detection, City of Hope
Dr. Sophie Pénisson has a background in mathematics and probability theory. Initially, her research focused on the theoretical aspects of certain mathematical objects (stochastic processes), eventually turning to their use in life science modeling. This led her to discover the impact of their application in cancer research, and she has since chosen to devote herself exclusively to this field.
Dr. Pénisson holds a French-German joint Ph.D. in Mathematics (French National Institute for Agricultural Research and Potsdam University). After a 10-year academic career at the University of Paris-Est (France), she joined TGen in October 2022 as an applied mathematician. She uses or develops the appropriate mathematical tools to model, understand and analyze the complexity of cancer evolution, in order to improve our early detection and risk prediction capabilities.
Evaluating cancer etiology and risk with a mathematical model of tumor evolution. S. Pénisson, A. Lambert, C. Tomasetti (2022), Nature Communications, Volume 13 n°7224
Why are viral genomes so fragile? The bottleneck hypothesis. N. Merleau, S. Pénisson, P. Gerrish, S. Elena, M. Smerlak (2021), PLOS Computational Biology, 17(7
Dynamics and fate of beneficial mutations under lineage contamination by linked deleterious mutations. S. Pénisson, T. Singh, P. Sniegowski and P. Gerrish (2017), Genetics, Volume 205 n°3
Beyond the Q-process: various ways of conditioning the multitype Galton-Watson process. S. Pénisson (2016), ALEA, Lat. Am. J. Probab. Math. Stat., Volume 13 n°1
Estimation of the infection parameter of an epidemic modeled by a branching process. S. Pénisson (2014), Electronic Journal of Statistics, Volume 8 n°2