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Open AccessArticle

A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales

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Centro de Investigación y Modelamiento de Fenómenos Aleatorios CIMFAV-Ingemat, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso 2340000, Chile
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Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaíso 2340000, Chile
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Departamento de Ecología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile
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Instituto de Ecología y Biodiversidad, Santiago 8331150, Chile
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Centre for Psychedelic Research, Department of Medicine, Imperial College London, London SW7 2DD, UK
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Data Science Institute, Imperial College London, London SW7 2AZ, UK
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Centre for Complexity Science and Department of Mathematics, Imperial College London, London SW7 2AZ, UK
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(10), 1009; https://doi.org/10.3390/e21101009
Received: 16 September 2019 / Revised: 13 October 2019 / Accepted: 14 October 2019 / Published: 16 October 2019
(This article belongs to the Special Issue Information Theory Applications in Biology)
Despite their differences, biological systems at different spatial scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are often hard to grasp due to the highly specialized nature of modern science and the parcelled terminology employed by various scientific sub-disciplines. To explore these common organizational features, this paper provides a comparative study of diverse applications of the maximum entropy principle, which has found many uses at different biological spatial scales ranging from amino acids up to societies. By presenting these studies under a common approach and language, this paper aims to establish a unified view over these seemingly highly heterogeneous scenarios. View Full-Text
Keywords: maximum entropy principle; biological systems across scales; model-free data analysis; inverse problems maximum entropy principle; biological systems across scales; model-free data analysis; inverse problems
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MDPI and ACS Style

Cofré, R.; Herzog, R.; Corcoran, D.; Rosas, F.E. A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales. Entropy 2019, 21, 1009.

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