PySB Models

Biochemical systems models encoded using the PySB framework:

PAR2 Activation and calcium signaling Reaction Model (PARM)

Models of agonist-induced activation of PAR2 and calcium signaling via the phospholipase C and IP3 pathway.

  • Type: Dynamical differential equation-based (ODE/SDE) model.
  • Language: Python via PySB
  • GitHub Repo: NTBEL/PARM

Model of Yeast Glycolitic Oscillations (MYGO)

PySB implementation of a simple model of yeast glycolytic oscillations adapted from Bier et al (Biophys. J. 78, 1087-1093, 2000; https://doi.org/10.1016/S0006-3495(00)76667-7).

  • Type: Dynamical differential equation-based (ODE/SDE) model.
  • Language: Python via PySB.
  • GitHub Repo: blakeaw/MYGO

Three-component repressive network model

PySB implementation of the generic three component repressor model described in Figure 1 of Mogilner et al. (Developmental Cell 11, 279-287, 2006; https://doi.org/10.1016/j.devcel.2006.08.004)

PK/PD models

PySB add-on for PK/PD modeling that includes some pre-defined PK pysb.pkpd.pk_models and PK/PD (pysb.pkpd.models) models.

  • Type: Dynamical differential equation-based (ODE) models.
  • Language: Python via PySB
  • GitHub Repo: blakeaw/pysb-pkpd

NEURON Models

Reaction-diffusion models encoded using the NEURON framework:

Extracellular diffusion models

Models of fluorescent dye and neuropeptide release and diffusion in the brain extracellular space.

Models for data fitting

Pharmacodynamic response models

Library of pharmacodynamic models of concentration and dose-response, inhibitor-response, and receptor-response that can be used for empirical fitting of response data.

Diffusion fitting models

Models for non-linear fitting of 2D fluorescence imaging data and estimation of diffusion coefficients based on point-source and/or quantal release models.

  • Type: Classes and functions for empirical fitting.
  • Language: Python
  • GitHub Repo: NTBEL/diffusion-fit