This is a Research Dataset associated with the journal article

@article{Yang2025,
  doi = {10.1371/journal.pone.0328261},
  url = {https://doi.org/10.1371/journal.pone.0328261},
  year = {2025},
  month = jul,
  publisher = {Public Library of Science},
  volume = {20},
  number = {7},
  pages = {1-25},
  author = {Zhechao Yang and Hao Gao and Godfrey L. Smith and Radostin D. Simitev},
  title = {Dominant Ionic Currents in Rabbit Ventricular Action Potential Dynamics},
  journal = {PLoS ONE}
}


ABSTRACT
 Mathematical models of cardiac cell electrical activity include
 numerous parameters, making calibration to experimental data and
 individual-specific modeling challenging. This study applies Sobol
 sensitivity analysis, a global variance-decomposition method, to identify
 the most influential parameters in the Shannon model of rabbit
 ventricular myocyte action potential (AP). The analysis highlights
 the background chlorine current as the dominant determinant
 of AP variability. Additionally, the inward rectifier potassium
 current, fast/slow delayed rectifier potassium
 currents, sodium-calcium exchanger
 current, the slow component of the transient
 outward potassium current, and L-type calcium
 current significantly affect AP biomarkers, including
 duration, plateau potential, and resting potential. Confidence
 intervals from bootstrapping validate the robustness of these
 results. Exploiting these results, a hierarchical reduction of the
 model is performed and  demonstrates that retaining only six key
 parameters can sufficiently capture individual biomarkers, with a
 coefficient of determination exceeding 0.9 for selected
 cases. These findings improve the utility of the Shannon model
 for personalized simulations, aiding applications like digital
 twins and drug response predictions in biomedical research. 

A suite of Python codes for a pipeline of 
sensitivity analysis of parameters in mathematical models of myocyte action potentials
can be found on https://github.com/ZhechaoYanggla/Code-for-sensitivity-analysis-of-parameters-in-mathematical-models-of-myocyte-action-potentials.

KEYWORDS
Cardiac action potential, rabbit ventricular myocyte, mathematical models, global sensitivity analysis


1) Data formats and software for analysis
The data is either in ".txt"/".npy" format or in the format of Python ".PY" files.
The code dependencies include standard Python libraries and the Myokit [myokit.org] and SALib [github.com/SALib)]. packages. 
All dependencies are declared in the code by Python "import" statements.


2) Description of datasets
* ./Sobol_paper-main/Sobol analysis/Sensitivity analysis.py    -  PYscripts for performing sensitivity analysis: --generate: Runs parameter generation --simulate: Runs simulations --analyze: Runs sensitivity analysis --all: Runs everything sequentially
* ./Sobol_paper-main/fig010/fig010.py   --- creates Fig.1
* ./Sobol_paper-main/fig020/fig020.py   --- creates Fig.2
* ./Sobol_paper-main/fig030/fig030.py   --- creates Fig.3
* ./Sobol_paper-main/fig040/fig040.py   --- creates Fig.4
* ./Sobol_paper-main/fig050/fig050.py   --- creates Fig.5
* ./Sobol_paper-main/fig060/fig060.py   --- creates Fig.6
* ./Sobol_paper-main/fig070/fig070.py   --- creates Fig.7
* ./Sobol_paper-main/fig080/fig080.py   --- creates Fig.8
* ./Sobol_paper-main/fig090/fig090.py   --- creates Fig.9