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Parameter estimation tabular data

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

This repository describes PEtab --- a data format for specifying parameter estimation problems in systems biology, provides a Python library for easy access and validation of PEtab files. See doc/ for more info.

About PEtab

PEtab is built around SBML and based on tab-separated values (TSV) files. It is meant as a standardized way to provide information for parameter estimation which is out of the current scope of SBML. This includes for example:

  • Specifying and linking measurements to models

    • Defining model outputs

    • Specifying noise models

  • Specifying parameter bounds for optimization

  • Specifying multiple simulation condition with potentially shared parameters


Where PEtab is used / supported:

PEtab support for D2D and AMIGO2 is under development.

If your project or tool is using PEtab, and you would like to have it listed here, please let us know.

Using PEtab

If you would like to use PEtab yourself, please have a look at doc/ or at the example models provided in the benchmark problem collection.

To convert your existing parameter estimation problem to the PEtab format, you will have to:

  1. Specify your model in SBML

  2. Set up model outputs and noise model using AssignmentRules as described in the PEtab documentation

  3. Create a condition table, if appropriate

  4. Create a table of measurements

  5. Create a parameter table

If you are using Python, some handy functions of the PEtab library can help you with that. This include also a PEtab validator called which you can use to check if your files adhere to the PEtab standard. If you have further questions regarding PEtab, feel free to post an issue at our github repository.

PEtab Python library

PEtab comes with a Python package for creating, checking, and working with PEtab files. This library is available on pypi and the easiest way to install it is running

pip3 install petab

It will require Python3.6 to run.

When setting up a new parameter estimation problem, the most useful tools will be:

  • The PEtab validator, which is now automatically installed using Python entrypoints to be available as a shell command from anywhere called petablint

  • petab.core.create_parameter_df to create the parameter table, once you have set up the model, condition table and measurement table

Extending PEtab

We are aware of the fact that PEtab may not serve everybody's needs. If you have a suggestion of how to extend PEtab, feel free to post an issue at our github repository.

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