DocumentCode :
260166
Title :
Comparison of complexity measures for DNA sequence analysis
Author :
Monge, Ricardo E. ; Crespo, Juan L.
Author_Institution :
Escuela de Cienc. de la Comput. e Inf., Univ. de Costa Rica, San Jose, Costa Rica
fYear :
2014
fDate :
16-18 July 2014
Firstpage :
71
Lastpage :
75
Abstract :
This paper looks into DNA analysis by computing and comparing complexity measures, in addition to providing a review of recent studies regarding the measurement of DNA complexity. The authors compare Shannon Entropy, Kolmogorov Complexity (approximated by Lempel-Ziv Compressibility) and statistical complexity, and observe that regions corresponding to genes have consistently different complexity measures (i.e., they are more regular) than those regions that do not have any gene associated with them. This provides insight on how to develop new tools for automated DNA analysis.
Keywords :
DNA; biology computing; computational complexity; DNA complexity; DNA sequence analysis; Kolmogorov complexity; Shannon entropy; complexity measures; statistical complexity; Bioinformatics; Complexity theory; DNA; Entropy; Genomics; Sea measurements; DNA entropy; coding and non-coding DNA; compressibility; entropy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-inspired Intelligence (IWOBI), 2014 International Work Conference on
Conference_Location :
Liberia
Type :
conf
DOI :
10.1109/IWOBI.2014.6913941
Filename :
6913941
Link To Document :
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