Optimal Therapeutic Methods with Random-Length Response in Probabilistic Boolean Networks Conference Paper uri icon

abstract

  • Any antitumor agent should act very rapidly with high level of efficiency so that it may increase the patient's chance of survival along with a reasonable quality of life during the course of treatment. The goal is to kill as many tumor cells as possible or shift them into a state where they can no longer proliferate. However, biological variabilities among cells in a population and the way they interact with each other or respond to a drug introduce randomness and uncertainty at different levels. This uncertainty should be modeled when designing an intervention strategy. In this paper, we implement a tumor growth model in the presence of the antitumor agent and characterize the variability in the drug response. Then, we present a methodology to devise optimal intervention policies for probabilistic Boolean networks when the antitumor drug has a random-length duration of action. 2012 IEEE.

name of conference

  • Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

published proceedings

  • 2012 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS)

author list (cited authors)

  • Yousefi, M. R., Datta, A., & Dougherty, E. R.

citation count

  • 0

complete list of authors

  • Yousefi, Mohammadmahdi R||Datta, Aniruddha||Dougherty, Edward R

publication date

  • December 2012