Artificial Evolution Methods in the Biological and Biomedical Sciences

Call for Papers

The biological and biomedical sciences are facing an information explosion and an understanding implosion. That is, our ability to generate information about biological systems is far outpacing our ability to make sense of it. Computational intelligence methods are needed now more than ever to facilitate the analysis and interpretation of mountains of data.

This special issue of the Journal of Artificial Evolution and Applications will focus on recent advances in artificial evolution methods such as agent-based modeling, artificial immune systems, estimation of distribution algorithms, evolutionary algorithms, genetic algorithms, genetic programming, and swarm intelligence for solving complex problems in the biological and biomedical sciences.

The aim is to attract papers that present new artificial evolution methods with application to biological and biomedical data and problems. Of particular interest are papers that analyze or model real data, that address the hierarchical complexity of biological systems and that provide a biological interpretation and/or experimental validation of the results.

Topics include (but are not limited to):

  • Data mining in biological or biomedical databases
  • Diagnostic or predictive testing in epidemiology and genetics
  • Functional diversification through gene duplication and exon shuffling
  • Gene expression and regulation, alternative splicing
  • Genetic association studies
  • Haplotype and linkage disequilibrium analysis
  • Image analysis and pattern recognition
  • Metabolomics and metabolic control analysis
  • Microarray analysis
  • Network reconstruction and modeling
  • Pharmacokinetic and pharmacodynamic analysis
  • Phylogenetic reconstruction and analysis
  • Relationships between evolved systems and their environment (e.g., phylogeography)
  • Relationships within evolved communities (cooperation, coevolution, symbiosis, etc.)
  • Sensitivity of speciation to variations in evolutionary processes
  • Sequence alignment and analysis
  • Simulation of cells, viruses, organisms, and whole ecologies
  • Structure prediction for biological molecules (structural biology)
  • Systems biology

Authors should follow the Journal of Artificial Evolution and Applications manuscript format described at the journal site http://www.hindawi.com/journals/jaea/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:

Manuscript DueOctober 1, 2008
First Round of ReviewsJanuary 1, 2009
Publication DateApril 1, 2009

Guest Editors

  • Janet Clegg, Department of Electronics, The University of York, York YO10 5DD, UK
  • Jason H. Moore, Department of Genetics, Dartmouth College, Lebanon, NH 03756, USA
  • Marylyn Ritchie, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
  • Stephen Smith, Department of Electronics, The University of York, York YO10 5DD, UK
  • Elena Marchiori, Faculty of Science, University of Nijmegen, Postbus 9010, 6500 GL Nijmegen, The Netherlands