The Parallel Genetic Algorithm for Designing DNA Randomizations in a Combinatorial Protein Experiment

  • Jacek Błażewicz
  • Beniamin Dziurdza
  • Wojciech T. Markiewicz
  • Ceyda Oğuz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3911)


Evolutionary methods of protein engineering such as phage display have revolutionized drug design and the means of studying molecular binding. In order to obtain the highest experimental efficiency, the distributions of constructed combinatorial libraries should be carefully adjusted. The presented approach takes into account diversity–completeness trade–off and tries to maximize the number of new amino acid sequences generated in each cycle of the experiment. In the paper, the mathematical model is introduced and the parallel genetic algorithm for the defined optimization problem is described. Its implementation on the SunFire 6800 computer proves a high efficiency of the proposed approach.


Genetic Algorithm Phage Display Parallel Genetic Algorithm Length Versus Protein Library 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jacek Błażewicz
    • 1
    • 2
  • Beniamin Dziurdza
    • 1
    • 2
  • Wojciech T. Markiewicz
    • 2
  • Ceyda Oğuz
    • 3
  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland
  2. 2.Institute of Bioorganic ChemistryPolish Academy of SciencesPoznańPoland
  3. 3.Department of Industrial EngineeringKoç UniversitySariyer, IstanbulTurkey

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