renz: R-Enzymology

Contains utilities for the analysis of Michaelian kinetic data. Beside the classical linearization methods (Lineweaver-Burk, Eadie-Hofstee, Hanes-Woolf and Eisenthal-Cornish-Bowden), features include the ability to carry out weighted regression analysis that, in most cases, substantially improves the estimation of kinetic parameters (Aledo (2021) <doi:10.1002/bmb.21522>). To avoid data transformation and the potential biases introduced by them, the package also offers functions to directly fitting data to the Michaelis-Menten equation, either using ([S], v) or (time, [S]) data. Utilities to simulate substrate progress-curves (making use of the Lambert W function) are also provided. The package is accompanied of vignettes that aim to orientate the user in the choice of the most suitable method to estimate the kinetic parameter of an Michaelian enzyme.

Version: 0.1.1
Depends: R (≥ 4.0.0)
Imports: graphics, stats, VGAM
Suggests: knitr, rmarkdown, testthat
Published: 2021-12-02
Author: Juan Carlos Aledo
Maintainer: Juan Carlos Aledo <caledo at uma.es>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: renz results

Documentation:

Reference manual: renz.pdf
Vignettes: Enzyme Kinetic Parameters
Michaelis-Menten and the Lambert W function
Linearized Michaelis-Menten Equations
Fitting the Michaelis-Menten Model
Integrated Michaelis-Menten Equation

Downloads:

Package source: renz_0.1.1.tar.gz
Windows binaries: r-devel: renz_0.1.1.zip, r-release: renz_0.1.1.zip, r-oldrel: renz_0.1.1.zip
macOS binaries: r-release (arm64): renz_0.1.1.tgz, r-release (x86_64): renz_0.1.1.tgz, r-oldrel: renz_0.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=renz to link to this page.