Title :
Study on the chaotic characteristics of protein sequences
Author_Institution :
Teaching & Res. Office, Jiangsu Coll. of Inf. Technol., Wuxi, China
Abstract :
In this paper, the nonlinear prediction technique is used to study chaotic sequences, random sequences and protein sequences. The chaotic sequences are from the specific logistic system, and protein sequences are selected from Class, Architecture, Topology, Homology (CATH) database. From the results of this method, it is found that protein sequences may be chaos. In order to verify this hypothesis, Protein sequences are translated into time series by using electron-ion interaction pseudopotential (EIIP) values. Then the largest Lyapunov exponents are computed for the time series, which are greater than zero. Thus we reach the conclusion: protein sequences have chaotic characteristics.
Keywords :
bioinformatics; chaos; molecular biophysics; proteins; random processes; CATH database; Class, Architecture, Topology, Homology database; Lyapunov exponents; chaotic characteristics; chaotic sequences; electron-ion interaction pseudopotential values; nonlinear prediction technique; protein sequences; random sequences; specific logistic system; Amino acids; Chaos; Nearest neighbor searches; Protein engineering; Proteins; Random sequences; Time series analysis; EIIP; chaos; nonlinear prediction technique; protein sequence; the largest Lyapunov exponent;
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6495-1
DOI :
10.1109/BMEI.2010.5639856
