Literature DB >> 12633463

Zipf's law in gene expression.

Chikara Furusawa1, Kunihiko Kaneko.   

Abstract

Using data from gene expression databases on various organisms and tissues, including yeast, nematodes, human normal and cancer tissues, and embryonic stem cells, we found that the abundances of expressed genes exhibit a power-law distribution with an exponent close to -1; i.e., they obey Zipf's law. Furthermore, by simulations of a simple model with an intracellular reaction network, we found that Zipf's law of chemical abundance is a universal feature of cells where such a network optimizes the efficiency and faithfulness of self-reproduction. These findings provide novel insights into the nature of the organization of reaction dynamics in living cells.

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Year:  2003        PMID: 12633463     DOI: 10.1103/PhysRevLett.90.088102

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  49 in total

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5.  Transcript profiling by 3'-untranslated region sequencing resolves expression of gene families.

Authors:  Andrea L Eveland; Donald R McCarty; Karen E Koch
Journal:  Plant Physiol       Date:  2007-11-16       Impact factor: 8.340

6.  Consistency principle in biological dynamical systems.

Authors:  Kunihiko Kaneko; Chikara Furusawa
Journal:  Theory Biosci       Date:  2008-04-22       Impact factor: 1.919

7.  On theoretical models of gene expression evolution with random genetic drift and natural selection.

Authors:  Osamu Ogasawara; Kousaku Okubo
Journal:  PLoS One       Date:  2009-11-20       Impact factor: 3.240

8.  Invariant distribution of promoter activities in Escherichia coli.

Authors:  Alon Zaslaver; Shai Kaplan; Anat Bren; Adrian Jinich; Avi Mayo; Erez Dekel; Uri Alon; Shalev Itzkovitz
Journal:  PLoS Comput Biol       Date:  2009-10-23       Impact factor: 4.475

9.  Reduction of dynamical biochemical reactions networks in computational biology.

Authors:  O Radulescu; A N Gorban; A Zinovyev; V Noel
Journal:  Front Genet       Date:  2012-07-19       Impact factor: 4.599

10.  Quantitative analysis of fission yeast transcriptomes and proteomes in proliferating and quiescent cells.

Authors:  Samuel Marguerat; Alexander Schmidt; Sandra Codlin; Wei Chen; Ruedi Aebersold; Jürg Bähler
Journal:  Cell       Date:  2012-10-26       Impact factor: 41.582

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