renz: An R package for the analysis of enzyme kinetic data.
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Abstract
Background: Complex enzymatic models are required for analyzing kinetic data
derived under conditions that may not satisfy the assumptions associated with
Michaelis–Menten kinetics.
Results: To fill the existing gap between highly specialized and general-purpose
software, we have developed an easy-to-use R package, renz, designed for accurate
and efficient estimation of enzyme kinetic parameters. The package provides different
methods that can be clustered into four categories, depending on whether they are
based on data fitting to a single progress curve (evolution of substrate concentration
over time) or, alternatively, based on the dependency of initial rates on substrate concentration
(differential rate equation). A second criterion to be considered is whether
the experimental data need to be manipulated to obtain linear functions or, alternatively,
data are directly fitted using non-linear regression analysis. The current program
is a cross-platform, free and open-source software that can be obtained from the CRAN
repository. The package is accompanied by five vignettes, which are intended to guide
users to choose the appropriate method in each case, as well as providing the basic
theoretical foundations of each method. These vignettes use real experimental data to
illustrate the use of the package utilities.
Conclusions: renz is a rigorous and yet easy-to-use software devoted to the analysis
of kinetic data. This application has been designed to meet the needs of users who are
not practicing enzymologists, but who need to accurately estimate the kinetic parameters
of enzymes. The current software saves time and minimizes the risk of making
mistakes or introducing biases due to uncorrected error propagation effects.
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Aledo, J.C. renz: An R package for the analysis of enzyme kinetic data. BMC Bioinformatics 23, 182 (2022). https://doi.org/10.1186/s12859-022-04729-4










