Identifying Desirable Function Perturbations in Signaling Pathways Through Stochastic Analysis

The logical representation and analyses of biological systems provide us with valuable insights. Inherent fluctuations play an important role in the long-term behaviors of biological systems. In this work, we mainly investigate the effects of function perturbations that might contribute to the development of effective therapies. We propose a stochastic model for one-bit perturbations and perform effective analyses of biological systems subjected to function perturbations. In addition, we also consider the scenario of a multibit perturbation (i.e., a one-bit perturbation occurring in multiple columns); thereby, we can determine the most effective column combination for the purpose of maximizing or minimizing the desired signal probability. Through stochastic analysis of the caspase3 signaling pathway, the corresponding practicability and effectiveness are demonstrated. Consequently, appropriate therapies can be determined to maximize or minimize the probability of caspase3 signaling.