In this section
Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@article{Cofré:2019:10.3390/e21101009,
author = {Cofré, R and Herzog, R and Corcoran, D and Rosas, FE},
doi = {10.3390/e21101009},
journal = {Entropy: international and interdisciplinary journal of entropy and information studies},
pages = {1--20},
title = {A comparison of the maximum entropy principle across biological spatial scales},
url = {http://dx.doi.org/10.3390/e21101009},
volume = {21},
year = {2019}
}
TY - JOUR
AB - 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.
AU - Cofré,R
AU - Herzog,R
AU - Corcoran,D
AU - Rosas,FE
DO - 10.3390/e21101009
EP - 20
PY - 2019///
SN - 1099-4300
SP - 1
TI - A comparison of the maximum entropy principle across biological spatial scales
T2 - Entropy: international and interdisciplinary journal of entropy and information studies
UR - http://dx.doi.org/10.3390/e21101009
UR - https://www.mdpi.com/1099-4300/21/10/1009
UR - http://hdl.handle.net/10044/1/74337
VL - 21
ER -
Data Science Institute
William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom
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