This is an example implementation of an extension of PEtab, for the specification of time-dependent conditions.

Clone this repository then install it into your Python (virtual) environment.

git clone --recurse-submodules https://github.com/dilpath/petab_timecourse
cd petab_timecourse
pip install -e .[examples]

The examples depend on AMICI for simulation and pyPESTO for optimization, but these are independent of the PEtab extension.

A TSV with sequences of experimental conditions/dosing regimes/etc.

• timecourseId: An ID for the timecourse.
• timecourse: A semicolon-delimited sequence of times and experimental conditions.
  • in the example, the timecourse starts at time t=0 with experimental condition c0. At t=5, experimental condition switches to c1. From t=50 onwards, experimental condition c2 is used.

How to specify parameter estimation problem when estimating time?

• a lot of possible flexibility...
  • use objectivePrior... to apply constraints to the values that each estimated time point can take
  • for consecutively estimated time periods
    • the lower bound of the next period should match the upper bound of the previous period
    • handle via PEtab Control

WIP

• all columns from normal PEtab parameters table
• timecourseIds
• conditionIds
• type
  • time to estimate the start time of the period
    • then ignore parameterId etc?!
  • value to estimate the value that the parameter takes during the period