Emergent Statistical Laws in Single-Cell Transcriptomic Data

@article{Lazzardi2021EmergentSL,
  title={Emergent Statistical Laws in Single-Cell Transcriptomic Data},
  author={Silvia Lazzardi and Filippo Valle and Andrea Mazzolini and Antonio Scialdone and Michele Caselle and Matteo Osella},
  journal={bioRxiv},
  year={2021}
}
Large scale data on single-cell gene expression have the potential to unravel the specific transcriptional programs of different cell types. The structure of these expression datasets suggests a similarity with several other complex systems that can be analogously described through the statistics of their basic building blocks. Transcriptomes of single cells are collections of messenger RNA abundances transcribed from a common set of genes just as books are different collections of words from a… 

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