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