From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities

The data folder contains the data files that were used in "From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities" project: - raw (clinical_Original.csv) and preprocessed clinical data (clinical_data.csv) - raw transcriptomic data (TCGA-noise-ENSG.csv) - breast Gtext data (Gtex-noiso-ENSG.csv) - fluxomic data generated from genome-scale metabolic model (flux-test.csv) - Raw count, metadata and preprocessed single-cell transcriptomic objects for validation (are also available at: https://drive.google.com/drive/folders/1KnE2knUyaMq-7DVrUaHJEBR2CdiDhNJw?usp=sharing) - Spatial transcriptomic data (Spatial_738811QB) for validation - Reactions mapping of fluxomic data Link to paper: https://www.sciencedirect.com/science/article/pii/S0010482525015483