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 |
timecourse |
---|---|
(Unique) [string] | [string] |
dummyId | 0:c0;5:c1;50:c2 |
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 conditionc0
. Att=5
, experimental condition switches toc1
. Fromt=50
onwards, experimental conditionc2
is used.
- in the example, the timecourse starts at time
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
- use
WIP
- all columns from normal PEtab parameters table
timecourseIds
conditionIds
type
time
to estimate the start time of the period- then ignore
parameterId
etc?!
- then ignore
value
to estimate the value that the parameter takes during the period