This is a list of recent software packages developed in our group, sometimes in collaboration with other external researchers. Click on the figures to access details, documentation and download links.

Questions and/or reporting of issues should be directed to the main developer of each package.


Global parameter Estimation with Automated Regularisation

GenSSI 2.0

Generating Series for testing Structural Identifiability


Parallel global optimization library


Advanced Modelling and Identification using Global Optimization


Parallel Reverse Engineering with Mutual information & Entropy Reduction


Visualization of Identifiability Problems in Dynamic Biochemical Models


a suite of benchmark problems for dynamic modelling in systems biology


Automatic optimal design in synthetic biology


a multiplatform toolbox for Global Optimization using Metaheuristics (old site, new site)

Older packages (SSmGO, DOTcvpSB, CRNreals, SensSB, GLOBALm, MITS, ACOmi) have been removed since they are no longer supported. However, email us is you would like to check their status.

In addition to these packages, in many papers we also provide the software necessary for computational reproducibility. These codes are not listed here (since they are not considered standalone packages) but can be found in the Publications section.

Finally, we have collaborated in other software initiatives, including:

  • STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition): a MATLAB toolbox that analyses the local structural identifiability, observability, and invertibility of (possibly nonlinear) dynamic models of ordinary differential equations (ODEs).

  • PEtab: a data format for specifying parameter estimation problems in systems biology

  • saCMM: self-adaptive Cooperative Multimethod library (parallel global optimization code)

  • saCeSS2: global mixed-integer optimization library for high-performance computing infrastructures

  • asynPDE: MPI asynchronous Parallel Differential Evolution