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{Cofre:2019:10.20944/preprints201907.0240.v1,
author = {Cofre, R and Herzog, R and Corcoran, D and Rosas, F},
doi = {10.20944/preprints201907.0240.v1},
title = {A comparison of the maximum entropy principle across biological spatial scales},
url = {http://dx.doi.org/10.20944/preprints201907.0240.v1},
year = {2019}
}
TY - JOUR
AB - Despite their obvious differences, biological systems at different scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are usually obscured by the parcelled terminology employed by various scientific sub-disciplines. To explore these commonalities, this papers a comparative study of diverse applications of the maximum entropy principle, ranging from amino acids up to societies. By presenting these studies under a common language, this paper establishes a unified view over seemingly highly heterogeneous biological scenarios.
AU - Cofre,R
AU - Herzog,R
AU - Corcoran,D
AU - Rosas,F
DO - 10.20944/preprints201907.0240.v1
PY - 2019///
TI - A comparison of the maximum entropy principle across biological spatial scales
UR - http://dx.doi.org/10.20944/preprints201907.0240.v1
UR - https://www.preprints.org/manuscript/201907.0240/v1
UR - http://hdl.handle.net/10044/1/73313
ER -
Data Science Institute
William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom
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