Welcome to BindCurve
This website contains documentation for bindcurve - a lightweight Python package for fitting and plotting of binding curves (dose-response curves). It contains logistic model for fitting \(\text{IC}_{50}\) or \(\text{logIC}_{50}\), and also exact polynomial models for fitting \(K_d\) from both direct and competitive binding experiments. Fixing lower and upper asymptotes of the models during fitting is supported, as well as fixing the slope in logistic model. Additionally, \(\text{IC}_{50}\) values can be converted to \(K_d\) using conversion models.
bindcurve is intended as a simple tool for Python-based workflows in Jupyter notebooks or similar tools. Even if you have never used Python before, you can fit your binding curve in less than 5 lines of code. The results can be conveniently plotted with another few lines of code or simply reported in formatted output.
bindcurve is currently in Alpha version. Changes to API might happen momentarily without notice. If you encounter bugs, please report them on GitHub.