Application of a Novel Numerical Simulation to Biochemical Reaction systems

MotivationOmics 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 processes can be 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 in https://binomial-simulation.com/en/python-program/. Contactsato@zeon.co.jp Supplementary InformationSupplementary data are available in this pdf file. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/552732v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@e45ceorg.highwire.dtl.DTLVardef@108ff6borg.highwire.dtl.DTLVardef@1b8cf75org.highwire.dtl.DTLVardef@3c49c8_HPS_FORMAT_FIGEXP M_FIG C_FIG