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PubMed · 14744119

Zipf's law and human transcriptomes: an explanation with an evolutionary model.

Osamu Ogasawara·Shoko Kawamoto·Kousaku Okubo
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Abstract

Detailed analysis of human gene expression data reveals several patterns of relationship between transcript frequency and abundance rank. In muscle and liver, organs composed primarily of a homogeneous population of differentiated cells, they obey Zipf's law. In cell lines, epithelial tissue and compiled transcriptome data, only high-rankers deviate from it. We propose an evolutionary process model during which expression level changes stochastically proportionally to its intensity, providing a novel interpretation of transcriptome data and of evolutionary constraints on gene expression.

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Evolution, MolecularGenome, HumanHumansModels, TheoreticalTranscription, GeneticJournal Article

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Osamu Ogasawara, Shoko Kawamoto, Kousaku Okubo. Zipf's law and human transcriptomes: an explanation with an evolutionary model.. https://doi.org/10.1016/j.crvi.2003.09.031

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