Special Issue "Emergence of Information in Evolutionary Processes"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: closed (28 December 2011)
Prof. Dr. Kay Hamacher
AG Bioinformatics and theo. Biology Technische Universität Darmstadt, Schnittspahnstr. 10 64287 Darmstadt, Germany
Interests: computational biology; statistical biophysics; simulation and scientific computing; coarse-graining and multi-scale modeling; optimization
Biology has become a quantitative science and is seen more frequently as an information science with close links to computer science - culminating in the raise of bioinformatics and computational biology as well-established fields within biology and computer science itself.
The underlying dynamics of all biological process is evolution. Although mathematical models of evolution were introduced early on, the widespread availability of sequence and structural data opens new horizons for model derivation, method development and empirical insight in particular. New biology could nowadays be conceived by combining models and available data.
Now, evolutionary processes are inherently stochastic in nature, but at the same time they store, propagate, adapt, and combine information from aeons of selective pressure of competitors and the ecological environment. Information theoretical concepts and measures are therefore of fundamental importance to help evolutionary biology becoming quantitative.
This special issue of "Entropy" is devoted to this endeavor. We would like to publish novel research on:
- method development to quantify evolutionary processes
- information theoretical concepts to define evolutionary processes in a holistic fashion
- applications to open challenges in biology
- entropy concepts to understand adaption in natural and artificial systems
- entropy measures for drug resistance
- and novel ideas on the combination of information theory and evolution.
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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a 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.
- evolutionary dynamics
- stochastic processes
- biological and ecological networks
- network dynamics
- sequence entropy
- mutual information
- evolutionary operators
- host-parasite interaction
- viral-host evolution
Entropy 2011, 13(3), 570-594; doi:10.3390/e13030570
Received: 16 December 2010; in revised form: 19 February 2011 / Accepted: 22 February 2011 / Published: 25 February 2011| Download PDF Full-text (931 KB)
Article: Cellular Automata on Graphs: Topological Properties of ER Graphs Evolved towards Low-Entropy Dynamics
Entropy 2012, 14(6), 993-1010; doi:10.3390/e14060993
Received: 30 April 2012; in revised form: 31 May 2012 / Accepted: 31 May 2012 / Published: 5 June 2012| Download PDF Full-text (3051 KB)
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Cellular Automata on Graphs: Topological Properties of ER Graphs Evolved Towards Low-Entropy Dynamics
Authors: Carsten Marr and Marc-Thorsten Hütt
Affiliation: E-Mails: email@example.com; firstname.lastname@example.org
Abstract: Cellular automata (CA) are a remarkably efficient tool for exploring general properties of complex systems and spatiotemporal patterns arising from local rules. Totalistic cellular automata, where the update rules depend only on the density of states, are at the same time a versatile tool for also exploring dynamical processes on graphs. Here we briefly review our previous results on cellular automata on graphs, emphasizing some systematic relationships between network architecture and dynamics identified in this way. We then extend the investigation towards graphs obtained in a simulated-evolution procedure, starting from Erdös-Rényi (ER) graphs and selecting for low entropies of the CA dynamics. Our key result is a strong systematic association of low Shannon entropies and a broadening of the graph's degree distribution.
Last update: 29 December 2011