statkin

statkin is an R package designed for the statistical estimation and modeling of Michaelis-Menten enzyme kinetics and inhibition mechanisms.

Key features

• Linear Least Squares (michaelisLLS): Linearized Lineweaver-Burk parameter estimation via Ordinary (OLS) and Weighted Least Squares (WLS).
• Non-linear Least Squares (michaelisNLS): Direct regression via Ordinary (NLS) and Weighted Non-linear Least Squares (WNLS).
• Inhibition mechanism classification: Automated interaction testing (ANCOVA) to classify competitive, uncompetitive, and mixed/non-competitive mechanisms.
• Resampling techniques (michaelisBootstrap): Non-parametric residual bootstrapping for robust empirical percentile confidence intervals.

Installation

You can install the development version of statkin from GitHub with:

# install.packages("remotes")
remotes::install_github("itsmiguelrojas/statkin")

Basic Example

This basic example shows how to estimate kinetic parameters ($V_{max}$ and $K_M$) using direct Non-linear Least Squares:

library(statkin)

# Example substrate-velocity dataset
df_ctrl <- data.frame(
  s = c(1, 2, 5, 10, 20, 50),
  v = c(0.11, 0.19, 0.36, 0.51, 0.64, 0.74)
)

# Fit direct NLS model
fit <- michaelisNLS(df_control = df_ctrl)

# Display estimated parameters and standard errors
print(fit$parameters)
print(fit$standard_errors)

License

This project is licensed under the MIT License - see the LICENSE file for details.