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Using statistical methods to model the fine-tuning of molecular machines and systems
Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
Rekke forfattare: 22020 (engelsk)Inngår i: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 501, artikkel-id 110352Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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.

sted, utgiver, år, opplag, sider
2020. Vol. 501, artikkel-id 110352
Emneord [en]
Bayesian, Fine-tuning, Complexity, Specificity, Intelligent Design, Waiting time problem, Model selection
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Identifikatorer
URN: urn:nbn:se:su:diva-184334DOI: 10.1016/j.jtbi.2020.110352ISI: 000551665300011PubMedID: 32505827OAI: oai:DiVA.org:su-184334DiVA, id: diva2:1471960
Tilgjengelig fra: 2020-09-30 Laget: 2020-09-30 Sist oppdatert: 2022-02-25bibliografisk kontrollert

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