Ernest A. Fischer

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Methods for identifying differentially expressed genes were compared on time-series microarray data simulated from artificial gene networks. Select methods were further analyzed on existing immune response data of Boldrick et al. (2002, Proc. Natl. Acad. Sci. USA 99, 972-977). Based on the simulations, we recommend the ANOVA variants of Cui and Churchill.(More)
Methods for identifying differential expression were compared on time series microarray data from artificial gene networks. Identifying differential expression was dependent on normalization and whether the background was removed. Loess after background correction improved results for most methods. On data without background correction median centering(More)
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