Studying RNA dynamics from single-cell RNA sequencing snapshots
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Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41592-024-02366-8.pdf
Reference5 articles.
1. La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018). This paper uses quantification of unspliced and spliced mRNA molecules to trace cell lineages.
2. Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006). This article provides experimental evidence of transcriptional bursting in mammalian cells.
3. Gorin, G., Vastola, J. J. & Pachter, L. Studying stochastic systems biology of the cell with single-cell genomics data. Cell Syst. 14, 822–843 (2023). A paper outlining how to model stochastic systems of single-cell omics data.
4. Lopez, R., Regier, J., Cole, M. B., Jordan, M. I. & Yosef, N. Deep generative modeling for single-cell transcriptomics. Nat. Methods 15, 1053–1058 (2018). This method article presents a variational autoencoder for single-cell RNA sequencing data.
5. Yao, Z. et al. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex. Nature 598, 103–110 (2021). A paper that presents and analyzes multiple single-cell transcriptomic datasets from the mouse primary motor cortex.
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