Methods to predict protein spatial structure

Methods to predict protein spatial structure

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 pr...

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Veröffentlicht in:Cybernetics and systems analysis 2010, Vol.46 (1), p.34-50
Hauptverfasser: Sergienko, I. V., Ryazanov, V. V., Biletskyy, B. A., Byts, A. V., Gupal, A. M., Rzhepeskyy, S. S.
Format: Artikel
Sprache:eng
Schlagworte:
Amino acids
Analysis
Artificial Intelligence
Atoms & subatomic particles
Bayesian analysis
Control
Cybernetics
DNA
Energy
Genetics
Genomics
Hypotheses
Markov analysis
Mathematics
Mathematics and Statistics
Methods
Noise
Probability
Processor Architectures
Protein folding
Proteins
Software Engineering/Programming and Operating Systems
Studies
Systems Analysis
Systems Theory
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Beschreibung
Zusammenfassung: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.
ISSN:1060-0396
1573-8337
DOI:10.1007/s10559-010-9181-6