Omics · dataset · 2025
From bulk to single-cell and spatial data: An AI framework to characterise breast cancer metabolic dysregulations across modalities
Listed in Teesside University Research Data Repository
Description
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: 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)
Links
Where it is published
- DOI doi.org/10.17632/z53vvrwg74.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Cell metabolism · Computer Science & AI · Earth & Environmental Science · Life Sciences · Machine learning · Medicine & Health · Single-cell RNA sequencing
- Inferred from text
- Cancer 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/z53vvrwg74.1 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:310103 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Cell Metabolism'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:single-cell-rna-seq | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Single-Cell RNA Sequencing'] |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |