Abstract
AbstractMotivationOmics data and single-cell analyses have recently produced many biological informatics. These require simple, fast, and flexible numerical/analytical methods such as ordinary differential equations. However, formulating these equations and their computational processescanbe expensive and imprecise for simulating reactions involving genes and a small number of molecular systems. Therefore, developing a straightforward simulation method is necessary.ResultsWe developed a natural number simulation (NNS) method using binomial probability-based stochastic algorithms. Hence, this paper simulated one-gene systems for feedback and feed-forward reactions, allosteric biochemical reactions, and SIR-type population dynamics. Furthermore, NNS can calculate any biological reaction systems written using stoichiometric formula. Thus, NNS provides a comfortable simulation tool for the scientific and engineering fields; algorithms and applications are detailed using Python.Availability and implementationCalculation results and the program are available as supplementary information in binomial_v15.zip inhttps://binomial-simulation.com/en/python-program/.Contactsato@zeon.co.jpSupplementary InformationSupplementary data are available in this pdf file.Graphical Abstract
Publisher
Cold Spring Harbor Laboratory
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