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Detecting Periodic Genes from Irregularly Sampled Gene Expressions: A Comparison Study

机译:从不规则采样的基因表达中检测周期性基因的比较研究

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摘要

Time series microarray measurements of gene expressions have been exploited to discover genes involved in cell cycles. Due to experimental constraints, most microarray observations are obtained through irregular sampling. In this paper three popular spectral analysis schemes, namely, Lomb-Scargle, Capon and missing-data amplitude and phase estimation (MAPES), are compared in terms of their ability and efficiency to recover periodically expressed genes. Based on in silico experiments for microarray measurements of Saccharomyces cerevisiae, Lomb-Scargle is found to be the most efficacious scheme. 149 genes are then identified to be periodically expressed in the Drosophila melanogaster data set.
机译:已经利用基因表达的时间序列微阵列测量来发现参与细胞周期的基因。由于实验的限制,大多数微阵列观察是通过不规则采样获得的。在本文中,比较了三种流行的频谱分析方案,即Lomb-Scargle,Capon和缺失数据幅度和相位估计(MAPES),它们具有恢复周期性表达基因的能力和效率。根据用于酿酒酵母微阵列测量的计算机模拟实验,发现隆姆-斯卡格尔是最有效的方案。然后鉴定出149个基因在果蝇果蝇数据集中周期性表达。

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