Conformational transitions between functional states close or open ion conduction pathways. This behavior can be quantitatively described by the Hodgkin-Huxley formulation or by the Markov formulation. PyHH is a small Python library based on the Hodgkin-Huxley formulation for voltage-gated ion channels (VGICs) and the Markov model for ligand-gated ion channels (LGICs) as well as VGICs. Knowledge about Python programing is helpful, but not required. PyHH is small, but can be used for building very complicated neuron models. It is useful for patch clamper to better understand some important concepts in electrophysiology.

Why PyHH?

PyHH is written for patch clamper, and uses terms which are easily understood by those with patch clamp experience. In addition, it is easy to use. PyHH does not depend on other libraries. The tutorial materials help you start with PyHH. Just drop all the files in a folder where you want to use PyHH. I will update the the example scripts regularly.

There are 4 releases right now. Click release to download the latest version (v1.1).The files tutorial-NMDAR.pdf and tutorial-NMDAR.py were added with the new release.