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oai:data.mendeley.com/z53vvrwg74.1 2025-10-27T09:35:01Z

Occhipinti, Annalisa From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities Mendeley Data The data folder contains the data files associated with the publication Le Minh Thao Doan, Suraj Verma, Noushin Eftekhari, Claudio Angione, Annalisa Occhipinti. "From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities" Computers in Biology and Medicine, Volume 198, Part B, 2025, 111195, ISSN 0010-4825. DOI: https://doi.org/10.1016/j.compbiomed.2025.111195 This repository contains: - 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) Breast Cancer Machine Learning Cell Metabolism Single-Cell RNA Sequencing Spatial Transcriptomics Doan, Le Minh Thao Dataset doi:10.17632/z53vvrwg74.1 oai:data.mendeley.com/z53vvrwg74.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/z53vvrwg74 2025-10-27T09:35:01Z