Methods to predict protein spatial structure

Authors:
I. V. Sergienko;V. V. Ryazanov;B. A. Biletskyy;A. V. Byts;A. M. Gupal;S. S. Rzhepeskyy
Affiliations:
V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;A. A. Dorodnitsyn Computing Center of the Russian Academy of Sciences, Moscow, Russia;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
Venue:
Cybernetics and Systems Analysis
Year:
2010

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Abstract

Modern methods of predicting protein spatial structure are reviewed. Numerical results of predicting the secondary structure of protein on the basis of Bayesian recognition procedures on nonstationary Markov chains are discussed. Complementary principles of encoding genetic information in DNA and proteins are presented.