4.4 Article

Using statistical methods to model the fine-tuning of molecular machines and systems

期刊

JOURNAL OF THEORETICAL BIOLOGY
卷 501, 期 -, 页码 -

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ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2020.110352

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Bayesian; Fine-tuning; Complexity; Specificity; Intelligent Design; Waiting time problem; Model selection

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Fine-tuning has received much attention in physics, and it states that the fundamental constants of physics are finely tuned to precise values for a rich chemistry and life permittance. It has not yet been applied in a broad manner to molecular biology. However, in this paper we argue that biological systems present fine-tuning at different levels, e.g. functional proteins, complex biochemical machines in living cells, and cellular networks. This paper describes molecular fine-tuning, how it can be used in biology, and how it challenges conventional Darwinian thinking. We also discuss the statistical methods underpinning fine-tuning and present a framework for such analysis. (C) 2020 The Author(s). Published by Elsevier Ltd.

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