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From the third issue of 2017, Microarrays has changed its name to High-Throughput.

Open AccessArticle
Microarrays 2014, 3(3), 203-211;

A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven 5612 AZ,The Netherlands
Biometris, Wageningen University and Research Centre, Wageningen 6708 PB, The Netherlands
Wageningen Centre for Systems Biology, Wageningen 6700 AC, The Netherlands
Author to whom correspondence should be addressed.
Received: 24 March 2014 / Revised: 19 June 2014 / Accepted: 25 June 2014 / Published: 1 July 2014
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Microarray data is often utilized in inferring regulatory networks. Quantile normalization (QN) is a popular method to reduce array-to-array variation. We show that in the context of time series measurements QN may not be the best choice for this task, especially not if the inference is based on continuous time ODE model. We propose an alternative normalization method that is better suited for network inference from time series data. View Full-Text
Keywords: quantile normalization; histogram matching; time series quantile normalization; histogram matching; time series

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Astola, L.; Molenaar, J. A New Modified Histogram Matching Normalization for Time Series Microarray Analysis. Microarrays 2014, 3, 203-211.

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