A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

A New Modified Histogram Matching Normalization for Time Series Microarray Analysis

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 ...

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

cDNA Microarray Data Normalization

Experimental Design for Time-Series Microarray Analysis

Microarray experiments designed to analyze time-series gene expression levels are important to interpret the bacterial gene functions. For this purpose, two-color microarray is indispensable tool for viewing the gene expression changes as snapshot on a large scale. In two-color microarray experiments, differently labeled cDNAs derived from control and target samples are hybridized on an identic...

Unbiased Histogram Matching Quality Measure for Optimal Radiometric Normalization

Radiometric normalization is critical for multi-spectral image change detection. In this paper, a histogram matching method is proposed to perform relative radiometric normalization among heterogeneously sensed images. To quantify the histogram matching quality, which is reference image and band dependent, the image differencing based quantitative measure, such as Euclidean or Manhattan distanc...