Year: 2024
Type: article
Abstract: Motivation Omics 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. Results We 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 implementation Calculation results and the program are available as supplementary information in binomial_v15.zip in https://binomial-simulation.com/en/python-program/ . Contact [email protected] Supplementary Information Supplementary data are available in this pdf file. Graphical Abstract
Author: Takashi Sato
Institution: Zeon (Japan)
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,295
OpenAlex ID: W4402321429