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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
The use of genomic signal compression for classification and identification of organisms
 Sedlář, Karel ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
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.
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The use of genomic signal compression for classification and identification of organisms
 Sedlář, Karel ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
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.
Detailed record

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