Abstract
In biochemical reaction networks, the first passage time (FPT) of a reaction quantifies the time, from the initial state, that it takes for the reaction to first occur. While the mean FPT historically served as a summary metric, a far more comprehensive characterization of the dynamics of the network is contained within the complete FPT distribution. The relatively uncommon theoretical treatments of the FPT distribution that have been given in the past have been confined to linear systems with zero- and first-order processes. Recently, we presented mathematically exact solutions for the FPT distribution within nonlinear systems involving two-particle collisions, such as A + B → C. Although this research yielded invaluable results, it was based upon the assumption of initial conditions in the form of a Poisson distribution. This somewhat restricts its relevance to real-world biochemical systems, which frequently display intricate behavior and initial conditions that are non-Poisson in nature. Our current study extends prior analyses to accommodate arbitrary initial conditions, thereby expanding the applicability of our theoretical framework and providing a more adaptable tool for capturing the dynamics of biochemical reaction networks.
Funding Information
  • Natural Science Foundation of China Young Scientists Fund (12001111)
  • National Natural Science Foundation (11925103)
  • Shanghai Municipal Science and Technology Major Project (2018SHZDZX01)
  • 2021 STCSM (2021SHZDZX0103)
  • ZJ Lab and Shanghai Center for Brain Science and Brain-Inspired Technology, the 111 Project (B18015)

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