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Randomness in biology

Published online by Cambridge University Press:  28 March 2014

THOMAS HEAMS
THOMAS HEAMS*
Affiliation:
INRA - UMR 1313 - Génétique Animale et Biologie Intégrative, Domaine de Vilvert Bâtiment 211, 78352 Jouy-en-Josas cedex, AgroParisTech - Département Sciences de la Vie et Santé, 16 rue Claude Bernard, 75231 PARIS cedex 05, France Email: thomas.heams@agroparistech.fr
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Abstract

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Biology has contradictory relationships with randomness. First, it is a complex issue for an empirical science to ensure that apparently random events are truly random, this being further complicated by the loose definitions of unpredictability used in the discipline. Second, biology is made up of many different fields, which have different traditions and procedures for considering random events. Randomness is in many ways an inherent feature of evolutionary biology and genetics. Indeed, chance/Darwinian selection principles, as well as the combinatorial genetic lottery leading to gametes and fertilisation, rely, at least partially, on probabilistic laws that refer to random events. On the other hand, molecular biology has long been based on deterministic premises that have led to a focus on the precision of molecular interactions to explain phenotypes, and, consequently, to the relegation of randomness to the marginal status of ‘noise’. However, recent experimental results, as well as new theoretical frameworks, have challenged this view and may provide unifying explanations by acknowledging the intrinsic stochastic dimension of intracellular pathways as a biological parameter, rather than just as background noise. This should lead to a significant reappraisal of the status of randomness in the life sciences, and have important consequences on research strategies for theoretical and applied biology.

Type
Paper
Information
Mathematical Structures in Computer Science , Volume 24 , Special Issue 3: Developments of the Concepts of Randomness, Statistic and Probability , June 2014 , e240308
Copyright
Copyright © Cambridge University Press 2014 

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