PT  - JOURNAL ARTICLE
AU  - Heiko Enderling
TI  - Integrating experimental data to calibrate quantitative cancer models
AID  - 10.1101/032102
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 032102
4099  - http://biorxiv.org/content/early/2015/11/17/032102.short
4100  - http://biorxiv.org/content/early/2015/11/17/032102.full
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.