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Special Issue "Information Theory in Molecular Evolution: From Models to Structures and Dynamics"
Deadline for manuscript submissions: 31 January 2020.
2. Center for Systems Biology, University of Texas at Dallas, Richardson, TX, USA 3. Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
Interests: statistical inference; information theory; molecular evolution; structural bioinformatics; protein folding and function; biological networks; systems biology
The modern biological sciences are driven by information. Large amounts of experimental data are collected and synthetized to create models to explain the complexity of biological systems. In addition, inter- and intra-cellular information processing is key to understanding cellular physiology and disease. The study of evolution, and in particular molecular evolution, has benefited from information theoretical insights since the foundational work of Ronald A. Fisher. In recent years, there has been a growing interest in using tools from information theory and statistical physics to quantify and model evolutionary processes. An integration of quantitative evolutionary models with structural aspects of biomolecules has energized scientific contributions and discovery. Applications include the fields of protein structure prediction; protein folding; conformational plasticity in molecules; chromosome architecture and epistasis. Modern approaches also look at the study of dynamics and interactions within complexes that facilitate molecular recognition and catalytic specificity.
This Special Issue aims to collect novel contributions in this interdisciplinary field. We are especially interested in submissions that use information theoretical concepts as a core but are tightly integrated with the study of molecular processes. Applications may include novel evolutionary models, the application of phylogenetic signals to elucidate the biomolecular structure and function, and biomolecule engineering inspired by evolutionary cues. Also of interest for this issue are applications of entropy to the study of de novo gene birth, including the emergence of essential, taxonomically-restricted genes, as well as the dynamics of biomolecules, including molecular dynamics and biophysical modeling. Finally, biomedical applications related to mutational change and the use of statistical techniques to study viral evolution and disease are encouraged.
Appropriate submissions are encouraged from scientists with diverse and interdisciplinary backgrounds. Submissions should include examples of current or potential applications of entropy in biology or medicine with a special focus on molecular evolution. We encourage authors to make their contribution accessible to a wide range of science graduates, without compromising scientific content or flow. We also encourage the addition of a supplementary short (e.g. three minute) video that explains in plain language the general significance of the major finding(s).
Dr. Faruck Morcos
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 papers will be 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 1600 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.
- Evolutionary models
- Information metrics in evolution
- Amino acid coevolution
- Information content in molecular sequences
- Evolutionary landscapes
- Structure and dynamics of biomolecules
- Protein engineering
- Information processing in biological networks
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.
1. John Barton
2. Banu Ozkan
3. Martin Weigt
4. Claus Wilke
5. Emmanuel Martinez-Ledesma
6. Leandro Martinez
7. Tentative title: Serine-based beta-lactamases and Penicillin binding proteins evolution through simulation and machine learning analysis
Author: Peng Tao
Affiliation: Southern Methodist University.