Abstract
In this paper, we propose an efficient method based on spectral analysis for matching and retrieval of gene expression time series data. In this technique, we decompose a gene expression time series into a set of spectral components. The spectral parameters can then be used to compute the correlation between the expression data for a pair of genes using a closed-form mathematical equation. This method provides a reliable similarity metric for the comparison of gene expression data and can be used for efficient data retrieval.
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Yan, H. (2005). Efficient Matching and Retrieval of Gene Expression Time Series Data Based on Spectral Information. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424857_39
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DOI: https://doi.org/10.1007/11424857_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25862-9
Online ISBN: 978-3-540-32045-6
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