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DNA spectrograms express the periodicities of each of the four nucleotides A, T, C, and G in one or several genomic sequences to be analyzed. 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...
Probe design is the most important step for any microarray based assay. Accurate and efficient probe design and selection for the target sequence is critical in generating reliable and useful results. Several different approaches for probe design are reported in literature and an increasing number of bioinformatics tools are available for the same. However, based on the reported low accuracy, determining...
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...
DNA sequencing today produces vast amounts of image data in the final recording process. For example, Solexapsilas sequencing by synthesis platform allows the outcome of sequencing reactions to be observed simultaneously at a resolution of millions of individual DNA molecules. Recording the outcome after each reaction therefore, generates terabytes of image data in the course experimentation. For...
As applied to genomic sequence, spectral analysis is the application of Fourier transforms to binary indicator sequences derived from DNA sequence. After conversion to a color representation, the composition and harmonic properties of a sequence can be visualized. In previous work, these spectra have been used to identify sequence periodicities ranging from small to very large, both known and novel...
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