Inferring gene networks from discrete RNA counts across cells remains a complex problem. Following Bayesian non-parametrics, a computational framework is proposed to perform non-biased inference of transcription kinetics from single-cell RNA counting experiments.
References
Kilic, Z., Schweiger, M., Moyer, C., Shepherd, D. & Pressé, S. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00392-0 (2023).
Munsky, B., Neuert, G. & van Oudenaarden, A. Science 336, 183–187 (2012).
Sanchez, A., Choubey, S. & Kondev, J. Methods 62, 13–25 (2013).
Liu, J. et al. PLoS Comput. Biol. 17, e1008999 (2021).
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Choubey, S. Gene regulation meets Bayesian non-parametrics. Nat Comput Sci 3, 126–127 (2023). https://doi.org/10.1038/s43588-023-00405-6
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DOI: https://doi.org/10.1038/s43588-023-00405-6
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