title: Zipf's law and human transcriptomes: an explanation with an evolutionary model.
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.
authors.affiliation: Division of Gene Expression analysis, The Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Shizuoka, Japan.
authors.forename: Osamu
authors.initials: O
authors.lastname: Ogasawara
authors.forename: Shoko
authors.initials: S
authors.lastname: Kawamoto
authors.forename: Kousaku
authors.initials: K
authors.lastname: Okubo
mesh_terms: D019143:Evolution, Molecular; D015894:Genome, Human; D006801:Humans; D008962:Models, Theoretical; D014158:Transcription, Genetic