Mechanistic pathway models reveal how IL-10 generates pleiotropic immune responses

Processed experimental data, model initial conditions, and simulation outputs supporting the manuscript:

“Mechanistic pathway modeling reveals how IL-10 generates pleiotropic immune responses.”

This dataset enables full reproduction of the IL-10 signaling model, including:

• ABC-SMC model selection and parameter inference
• Dose-response simulations
• Immune dictionary's cell type simulations for STAT1/STAT3 activity
• Linear gene-specific models and binding parameter datasets

The dataset is organized into structured directories containing:

• /SS_search: Pickle files used to get the simplified steady states with the linear framework
• /data/ABC_SMC: Data used by the ABC_SMC model selection and parameter inference, contains initial values and bounds
• /data/binding: Binding rates used by the model (trained and untrained values)
• /data/expression: bulkRNAseq/proteomics data on receptors/STAT used to train/test the linear models and as initial conditions for the IL-10 signaling model
• /data/lin_models: Parameters of the gene-specific linear models
• /data/signaling: Data on dose-response curves used to train/test the IL-10 signaling model and RNAseq data used in the gene regulation section
• /data/uniprot: Data on uniprot ids
• /results/ABC_SMC: Results of the ABC_SMC model selection and parameter inference
• /results/ABC_SMC: Results of the IL-10 signaling model simulations on the train and test dose-response curves data with the fitted parameter values
• /results/immune_dict: Results of the IL-10 signaling model simulations on the cell types of the immune dictionary for STAT3 and STAT1
• /results/raw_param: Results of the IL-10 signaling model simulations on the train and test dose-response curves data with the raw parameter values
• /results/raw_param: Results of the slopiness analysis on the 3 IL-10 signaling models

Reproduction Instructions:

1. Clone repository:

   git clone git@github.com:Quim98/IL10_model_publication.git
   cd IL10_model_publication

2. Download the dataset and place it in the repo's folder

   
3. Create an environment and activate it:

   mamba env create -f environment.yaml
   mamba activate IL10_model

4. Run the scripts and notebooks!