Title :
On the modeling of heterogeneity in cancer tissue
Author :
Mohanty, Anwoy Kumar ; Datta, Amitava ; Venkatraj, Jijayanagaram
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
An important problem in the study of cancer is the understanding of the heterogeneous nature of the cell population. The clonal evolution of the tumor cells results in the tumors being composed of multiple sub-populations. Each sub-population reacts differently to any given therapy. This calls for the development of novel (regulatory network) models, which can accommodate heterogeneity in cancerous tissues. In this paper we present a new approach to model heterogeneity in cancer. We model heterogeneity as an ensemble of deterministic Boolean networks based on prior pathway knowledge. We develop the model considering the use of qPCR data. By observing gene expressions when the tissue is subjected to various stimuli, the compositional breakup of the tissue under study can be determined. We demonstrate the viability of this approach by using our model on synthetic data.
Keywords :
Boolean algebra; cancer; cellular biophysics; genetics; genomics; physiological models; tumours; cancer tissue heterogeneity modeling; cell regulatory network models; deterministic Boolean networks; gene expressions; prior pathway knowledge; qPCR data; tumor cells; Cancer; Computational modeling; Data models; Educational institutions; Gene expression; Medical treatment; Tumors; Bayesian methods; Markov Chain Monte Carlo; heterogeneity;
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2013 IEEE International Workshop on
Conference_Location :
Houston, TX
Print_ISBN :
978-1-4799-3461-4
DOI :
10.1109/GENSIPS.2013.6735916