Journal
PHYSICS LETTERS A
Volume 360, Issue 1, Pages 174-178Publisher
ELSEVIER
DOI: 10.1016/j.physleta.2006.07.076
Keywords
stochastic process; scaling-law; gene expression; Ito-Stratonovich calculus
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Large-scale acquisition technologies in mRNA abundance (gene expression) have provided new opportunities to better understand many complex biological processes. Lately, it has been reported that the observed gene expression data in several organisms significantly deviates from a Poisson distribution and follows a power-law or fat-tailed distribution. Here, we show that a simple stochastic model of gene expression with intrinsic and extrinsic noise derives the stationary power-law distribution using the Stratonovich calculus. Furthermore, we connect the experimental measure of the power-law exponent with the value of the mRNA decay. Finally, we compare the results with other models where stochastic equations were used within the Ito interpretation. (c) 2006 Elsevier B.V. All rights reserved.
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