Stochastic Gene Expression and the Processing and Propagation of Noisy Signals in Genetic Networks
作者： Daniel A. Charlebois , Theodore J. Perkins , Mads Kaern
DOI: 10.1007/978-3-642-19621-8_5
关键词: Gene 、 Bayesian inference 、 Computational biology 、 Biology 、 Artificial intelligence 、 Gene expression 、 Machine learning 、 Expression (mathematics) 、 Variation (game tree)
摘要: Over the past few years, it has been increasingly recognized that stochastic mechanisms play a key role in dynamics of biological systems. Genetic networks are one example where molecular-level fluctuations particular importance. Here stochasticity expression gene products can result genetically identical cells displaying significant variation biochemical or physical attributes. This influence individual and population-level fitness.
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