Name
Abstract | ||
|---|---|---|
DNA spectral analysis can be applied to systematically investigate DNA patterns, which may correspond to relevant biological features. As opposed to looking at nucleotide sequences, spectrogram analysis may detect structural characteristics in very long sequences that are not identifiable by sequence alignment. Clustering of DNA spectrograms can be used to perform spectral analysis of very large sequences or entire genomes, at different resolutions. Standard clustering algorithms have been used in spectral analysis to find strong patterns in spectra. However, as they use a global distance metric, those algorithms can only detect strong patterns coexisting in several frequencies. In this paper we propose a new method and several algorithms for aligning spectra suitable for efficient spectral analysis and allowing for the easy detection of strong patterns in both single frequencies and multiple frequencies. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/BIBM.2008.15 | Philadelphia, PA |
Keywords | DocType | ISSN |
digital library,biomedical literature,spectral analysis,class-attribute mining,dna sequences,novel text mining problem,sequence alignment,dna,sorting,genomics,nucleotide sequence,molecular biophysics,distance metric,dna sequence | Conference | 2156-1125 |
ISBN | Citations | PageRank |
978-0-7695-3452-7 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bucur, A. | 1 | 0 | 0.34 |
| J. Van Leeuwen | 2 | 308 | 55.29 |
| Dimitrova, N. | 3 | 0 | 0.34 |
| Mittal, C. | 4 | 0 | 0.34 |