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Evolutionary Computational Support for the Characterization of Biological Systems-Chapter 13

Elsevier Inc.
DOI: 10.1016/b978-155860797-2/50015-9
  • Biology
  • Computer Science
  • Medicine


Publisher Summary Evolutionary computation can be of considerable use in interpreting and analyzing spectra of biological systems. This chapter focuses on the electron paramagnetic resonance (EPR) technology, and on the use of an evolutionary computational approach to aid the characterization of biological systems with EPR. EPR spectroscopy is a non-destructive inspection method capable of detecting changes in organisms caused by biologically active substances or resulting from pathological conditions. Interpretation of spectral characteristics, which was performed manually in the past, is currently supported by numerical spectrum-simulation models. To find appropriate values of model parameters that reveal important information about the system being studied, an evolutionary algorithm is employed. Population-based evolutionary search is a good candidate for automating parameter optimization in EPR spectroscopy. To verify this idea, a spectrum-simulation model is integrated with an evolutionary algorithm and a preliminary experimental verification on synthetic EPR spectra is carried out.

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