RT Journal Article
SR Electronic
T1 Integrating experimental data to calibrate quantitative cancer models
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 032102
DO 10.1101/032102
A1 Heiko Enderling
YR 2015
UL http://biorxiv.org/content/early/2015/11/17/032102.abstract
AB For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. Experimental data can be utilized to calibrate model dynamics rates or rate constants. Proper integration of experimental data, however, depends on the chosen theoretical framework. Using live imaging of cell proliferation as an example, we show how to derive cell cycle distributions in agent-based models and averaged proliferation rates in differential equation models. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer cells.