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 [e-mail]: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!