Modern classification of organisms is performed on molecular data. These methods rely on multiple alignment of sequences of characters which make them computationally demanding. Only small parts of genomes can be compared in reasonable time. In this paper, the novel algorithm based on conversion of the whole genome sequences to cumulative phase signals is presented. Dyadic wavelet transform is used for lossy compression of signals by redundant frequency bands elimination. Signal classification is then performed as a cluster analysis using Euclidian metrics where multiple alignment is replaced by dynamic time warping.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:220018 |
Date | January 2013 |
Creators | Sedlář, Karel |
Contributors | Vítek, Martin, Škutková, Helena |
Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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