Monte Carlo approach to one-dimensional cell proliferation within a tissue-cell population


The interplay of biological, chemical, and physical factors of cancer cells give rise to its complex behavior. This complexity is one of the main reasons why the cure for cancer remains elusive. Finding a way to predict and understand this stochastic behavior would enable us to develop new and effective treatments that would hopefully lead to a cure for cancer. With this in mind, we constructed an algorithm for a stochastic one-dimensional cell proliferation through agent-based modeling and Monte Carlo methods. The proliferation of cells in a one-dimensional axis is demonstrated for different growth rates and cell-cell attraction strengths.