scRNA-Seq

e.g. IL6; SIRT6;

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Wang, S., Yao, X., Ma, S. et al. (2021). A single-cell transcriptomic landscape of the lungs of patients with COVID-19. Nat Cell Biol. https://doi.org/10.1038/s41556-021-00796-6
Ma, S., Sun, S., Geng, L., Song, M., Wang, W., Ye, Y., Ji, Q., Zou, Z., Wang, S., He, X., et al. (2020). Caloric Restriction Reprograms the Single-Cell Transcriptional Landscape of Rattus Norvegicus Aging. Cell 180, 984-1001.e1022
Wang, S., Zheng, Y., Li, J., Yu, Y., Zhang, W., Song, M., Liu, Z., Min, Z., Hu, H., Jing, Y., et al. (2020). Single-Cell Transcriptomic Atlas of Primate Ovarian Aging. Cell 180, 585-600.e519.
Zhang, W., Zhang, S., Yan, P., Ren, J., Song, M., Li, J., Lei, J., Pan, H., Wang, S., Ma, X., et al. (2020). A Single-cell Transcriptomic Landscape of Primate Arterial Aging. Nat Commun 11, 2202.
Li, J., Zheng, Y., Yan, P., Song, M., Wang, S., Sun, L., Liu, Z., Ma, S., Belmonte, J.C.I., Chan, P., et al. (2020). A Single-cell Transcriptomic Atlas of Primate Pancreatic Islet Aging. National Science Review. https://doi.org/10.1093/nsr/nwaa127
He, X., Memczak,S., Qu, J., Belmonte, J.C.I., Liu, G. (2020). Single-cell Omics in Ageing: A Young and Growing Field. Nature Metabolism 2, 293–302.

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Tissue Types

Single-cell transcriptomics

The single-cell transcriptomics module systematically reflects the tissue and cell type-specific heterogeneous changes in gene expression with age. This module provides high-resolution comprehensive reference maps of different cell types/subtypes, as well as information on their temporal and spatial distribution and gene expression patterns under different aging-related or disease conditions.

Data Submission

e.g. IL6; SIRT6;

Data Statistics

Deposit data into AA