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Evolutionary Biology from an Information Theory Approach

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Evolutionary Biology".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1753

Special Issue Editor


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Guest Editor
Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain
Interests: population genomics; evolutionary theory; simulation; information theory; evolutionary patterns

Special Issue Information

Dear Colleagues,

The mathematical theory of information began with the publication by the mathematician Claude Shannon of an article in 1948 where he formalizes the process of information exchange in message communication. It soon became clear that the theory had much broader applications. In biology, it was adopted by ecology and population genetics to measure species diversity, and more recently, it has had a significant impact in fields such as neurobiology and bioinformatics. In evolutionary biology, the basic equations of population genetics describing changes in gene frequency can be reformulated in terms of information. Additionally, the connection of information theory with the evolution of biological complexity and molecular biology has also been described. Recent studies seem to show that information theory may be the appropriate framework to describe evolutionary processes.

This Special Issue aims to contribute to the theoretical development of certain aspects of population genetics from the perspective of information theory. The objective is related to the connection between information and biological evolution. This relationship can be studied at various levels, such as information and changes in gene frequencies within the population, the organization of nucleotide sequences in DNA, information accumulated through natural selection, information in animal behavior, in the evolution of plants, in ecosystem interactions, and so on.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: any aspect of evolutionary biology connected with information theory.

I/We look forward to receiving your contributions.

Prof. Dr. Antonio Carvajal-Rodríguez
Guest Editor

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Keywords

  • evolution
  • population genetics
  • information
  • Kullback–Leibler
  • Jeffreys divergence
  • population stability index

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Published Papers (1 paper)

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Review

16 pages, 1378 KiB  
Review
Pan-Evo: The Evolution of Information and Biology’s Part in This
by William B. Sherwin
Biology 2024, 13(7), 507; https://doi.org/10.3390/biology13070507 - 8 Jul 2024
Viewed by 1217
Abstract
Many people wonder whether biology, including humans, will benefit or experience harm from new developments in information such as artificial intelligence (AI). Here, it is proposed that biological and non-biological information might be components of a unified process, ‘Panevolution’ or ‘Pan-Evo’, based on [...] Read more.
Many people wonder whether biology, including humans, will benefit or experience harm from new developments in information such as artificial intelligence (AI). Here, it is proposed that biological and non-biological information might be components of a unified process, ‘Panevolution’ or ‘Pan-Evo’, based on four basic operations—innovation, transmission, adaptation, and movement. Pan-Evo contains many types of variable objects, from molecules to ecosystems. Biological innovation includes mutations and behavioural changes; non-biological innovation includes naturally occurring physical innovations and innovation in software. Replication is commonplace in and outside biology, including autocatalytic chemicals and autonomous software replication. Adaptation includes biological selection, autocatalytic chemicals, and ‘evolutionary programming’, which is used in AI. The extension of biological speciation to non-biological information creates a concept called ‘Panspeciation’. Panevolution might benefit or harm biology, but the harm might be minimal if AI and humans behave intelligently because humans and the machines in which an AI resides might split into vastly different environments that suit them. That is a possible example of Panspeciation and would be the first speciation event involving humans for thousands of years. This event will not be particularly hostile to humans if humans learn to evaluate information and cooperate better to minimise both human stupidity and artificial simulated stupidity (ASS—a failure of AI). Full article
(This article belongs to the Special Issue Evolutionary Biology from an Information Theory Approach)
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