Information Theory Applications in Biology
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 14314
Special Issue Editors
Interests: theoretical ecology; ecological network analysis; information theory in ecology; metaphysics of ecology; dialogue between science & religion
2. The Santa Fe Institute, Santa Fe, NM 87131, USA
Interests: theoretical ecology; the emergence of social complexity; integration of theories in ecology
Interests: climate change ecology; biodiversity and biodiversity change; marine community ecology; metabolic scaling and metacommunity processes
2. The Santa Fe Institute, Santa Fe, NM 87131, USA
Interests: climate–ecosystem linkages; understanding patterns in the distribution and abundance of species across spatial scales and across habitats and taxonomic groups; using MaxEnt to develop unified and parsimonious theory of the distribution, abundance, and energetics of species in both static and dynamic ecosystems
Special Issues, Collections and Topics in MDPI journals
Interests: ecology; evolutionary rescue; biodiversity change; metacommunities; connectivity
Special Issue Information
Dear Colleagues,
It was Walter Elsasser who reminded us that physics is predicated entirely upon the treatment of homogeneous (identical) objects, whereas biology deals with massive heterogeneities. Iconic physical models deal with systems that interact at most weakly, while ecosystems links are strong and defining. Information theory shows promise for complementing conventional dynamics in our pursuit of understanding ecosystem behavior.
Information, or the difference that makes a difference, deals explicitly with differences among distributions of heterogeneous classes. Combining information theory with network representation, for example, allows one to treat significant interactions among disparate groups. Moreover, in biology, stochasticity is ever present, and thus information theory, which is predicated upon the absence of certainty, provides a natural and appropriate means of investigation.
To facilitate how information theory can complement conventional ecosystems science, the Multidisciplinary Digital Publishing Institute (MDPI) is inviting contributions to a volume entitled, “Information Theory Applications in Biology”. Information as considered in biology appears in three distinct manifestations. Firstly, there is the very apparent presence of information among species genomes and as transmitted in visual, audible, olfactory, and sensory cues. There is also information that inheres in the very dynamical structure of ecosystems that can be estimated and used to quantify the organizational status of a system, its loci of limiting interactions, and the prognostication of structural changes. In addition, the variational principle of Maximum Entropy that combines information theory and statistics has become a powerful tool in our understanding of physical and biological systems, in particular to tackle the fundamental challenge of making inferences under limited knowledge. New contributions that critically apply the principle of Maximum Entropy to problems in biology or biophysics, compare it with other methods or approaches, extend and modify it to deal with phenomena for which it has not yet been successfully applied, or review its use in a particular scientific domain within biology are encouraged. Submissions are sought in any of these three categories, and those that emphasize quantitative treatments are especially welcomed.
Appropriate contributions are encouraged from a wide range of investigators, including biologists, physical scientists, and mathematicians. Submissions should include examples of current or potential applications of information theory in biology or medicine. Authors are encouraged to make their contribution accessible to a wide range of science graduates, without compromising scientific content or flow, for example, via a table of symbols and jargon, and to include definitions understandable to most science graduates. The addition of a supplementary short (e.g., three minute) video, explaining in plain language the general significance of the major finding(s), would be especially valuable.
Prof. Robert E. Ulanowicz
Prof. Pablo A. Marquet
Dr. Mary I. O'Connor
Prof. John Harte
Prof. Andrew Gonzalez
Dr. Andrew Rominger
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
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