Abstract

Citation

Researchers should cite this work as follows:

• Enderling, H. (2023). 2015-Heiko_Enderling-Integrating experimental data to calibrate quantitative cancer models. SIMIODE, QUBES Educational Resources. doi:10.25334/Y6GY-6157

  BibTex | EndNote

Article Context

Description

Enderling, Heiko. 2015. Integrating experimental data to calibrate quantitative cancer models. Preprint.  3 pp.

See https://www.biorxiv.org/content/10.1101/032102v1. Accessed 29 March 2023.

Abstract:  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.

Keywords:  agent based, data, cancer, tumor, parameter estimation, differential equation, system, model , fitting, parameter estimation