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Many cellular processes exhibit cyclic behaviors. Hence, one important task in gene expression data analysis is to detect subset of genes that exhibit periodicity in their gene expression time series profiles. Unfortunately, gene expression time series profiles are usually of very short length, with very few periods, unevenly sampled, and are highly contaminated with noise. This makes detection of...
Spectrum estimation is a popular method for identifying periodically expressed genes in microarray time series analysis. For unevenly sampled data, a common technique is applying the Lomb-Scargle algorithm. The performance of this method suffers from the effect of noise in the data. In this paper, we propose a new spectrum estimation algorithm for unevenly sampled data. The new method is based on...
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