Data-driven Computational Modelling

Hasenauer Lab @ University of Bonn (formerly at Helmholtz Munich)

Hi there 👋

This is the GitHub organization of the Hasenauer Lab at University of Bonn, Germany.

For our research in computational biology, we developed a number of tools, mostly around simulation of dynamical models and parameter inference.

The highlights are:

pypesto for parameter estimation in Python
PEtab for specifying parameter estimation problems in systems biology in an efficient and interoperable manner
AMICI for scalable simulation and sensitivity analysis (Python / C++ (/ Matlab))
pyABC for distributed and scalable ABC-SMC (Approximate Bayesian Computation - Sequential Monte Carlo) for parameter estimation of complex stochastic models (Python)

pyABC pyABC Public

distributed, likelihood-free inference

Python 216 46
pyPESTO pyPESTO Public

python Parameter EStimation TOolbox

Python 266 47
parPE parPE Public

Parameter estimation for dynamical models using high-performance computing, batch and mini-batch optimizers, and dynamic load balancing.

C++ 22 4
PESTO PESTO Public

PESTO: Parameter EStimation TOolbox, Bioinformatics, btx676, 2017.

MATLAB 27 12