9 citations · 13 across the 5 of their papers we have counts for
5 papers
Using birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data
C. Wu, E. B. Gunnarsson, E. M. Myklebust +6
Tumor heterogeneity is a complex and widely recognized trait that poses significant challenges in developing effective cancer therapies. In particular, many tumors harbor a variety…
Modeling of mouse experiments suggests that optimal anti-hormonal treatment for breast cancer is diet-dependent
Tuğba Akman, Lisa M. Arendt, Jürgen Geisler +3
Estrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown…
ABC of the Future
Henri Pesonen, Umberto Simola, Alvaro Köhn-Luque +8
Approximate Bayesian computation (ABC) has advanced in two decades from a seminal idea to a practically applicable inference tool for simulator-based statistical models, which are…
A scalable solver for a stochastic, hybrid cellular automaton model of personalized breast cancer therapy
Xiaoran Lai, Håkon A. Taskén, Torgeir Mo +4
Mathematical modeling and simulation is a promising approach to personalized cancer medicine. Yet, the complexity, heterogeneity and multi-scale nature of cancer pose significant c…
Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights
J. C. L. Alfonso, A. Kohn-Luque, T. Stylianopoulos +3
There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumou…