Error Models For Microarray Intensities

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Error models for microarray intensities. W. Huber, A. von Heydebreck, and M. Vingron. Encyclopedia of Genomics, Proteomics and Bioinformatics. John Wiley & sons (2005).

Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model.

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Error models for microarray intensities – Bepress – 1 Motivation An error model is a description of the possible outcomes of a measurement. It depends on the true value of the underlying quantity that is measured and.

The systematic error introduced by microarray experiments mainly involves spot intensity-dependent, feature-specific and spot position-dependent contributions.

The primary objective of microarray study is to determine. error models. i array. Our main interest here is to char- acterize the intensity error e(i, j). The error.

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Microarray normalization and error models. mRNA concentrations and intensities o other array. Error models for microarray intensities. W. Huber, A. von.

Testing for Differentially-Expressed Genes by Maximum. –. under the model, these intensities are. as is the use of the error model to compare the within- and. Large error models for microarray intensities.

title = {Year Paper Error models for microarray intensities}, year = {}} netics This working paper site is hosted by The Berkeley Electronic Press (bepress).

We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we obtain a statistic whose variance is approximately independent of the.

We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we.

1. Motivation An error model is a description of the possible outcomes of a measurement. It depends on the true value of the underlying quantity that is measured and.

Some of the strongest hurricanes in western Atlantic history have reached their peak intensities while. there is greater model divergence on what will happen with.

Mixed Models Analysis of Microarray Experiments Using. Pooled Error Estim ates. experiments to include the possibility of similar error distributions among groups of. VG)( represent levels of signal intensity for genes that can specifically be.

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