A Single-Cell Transcriptomic Atlas of Human Skin Aging
This dataset contains structured tables extracted from the supplementary materials of the publication:
"A single-cell transcriptomic atlas of human skin aging"
Cell Reports, 2020
DOI: 10.1016/j.celrep.2020.108132
The data has been processed from the publication PDF into a .parquet file to facilitate downstream analysis and integration into machine learning workflows.
📦 Dataset Description
The dataset includes multiple tables capturing aging-related transcriptomic changes in human skin tissue at the single-cell level. Tables were extracted using PDF parsing tools and contain gene expression summaries and annotations useful for skin biology and aging research.
🔧 Usage Instructions
To load the Parquet file in Python:
import pandas as pd
df = pd.read_parquet("skin_aging_data.parquet")
print(df.head())
🚀 Use Cases
- Aging biomarker discovery in dermal and epidermal compartments
- Training skin-specific biological age predictors
- Integrating skin aging profiles with other tissue atlases
- Cross-species comparison of skin aging signatures
- Evaluation of anti-aging interventions at single-cell resolution
📖 Citation
If you use this dataset, please cite:
Xie, W., et al. A single-cell transcriptomic atlas of human skin aging. Cell Reports, 2020.
DOI: 10.1016/j.celrep.2020.108132
🙏 Acknowledgments
This dataset was curated and converted by Iris Lee for open access machine learning research in aging biology and skin regeneration. ### 🧑💻 Team: MultiModalMillenials. Iris Lee (@iris8090)
Source publication by Xie et al. (2020) — Cell Reports.