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C R Biol. 2003 Oct-Nov;326(10-11):1097-101.

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

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  • 1Division of Gene Expression analysis, The Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Shizuoka, Japan.

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.

PMID:
14744119
[PubMed - indexed for MEDLINE]
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