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Data mining is frequently used method for analyzing road accident data in present research.
The bisulfite genomic sequencing protocol is a widely used method for analyzing DNA methylation.
Logistic regression is the most commonly used method for analyzing case control studies.
Clustering EST sequences is a widely used method for analyzing the transcriptome of a genome.
Since the characterization of the eye's monochromatic aberration fluctuations in 2001, the power spectrum has remained the most widely used method for analyzing their dynamics.
Germ-line transformation of insects is now a widely used method for analyzing gene function and for the development of genetically modified strains suitable for pest control programs.
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For the last few decades RTA, i.e., modern DCA, using typecurve is one of the developed and most used methods for analyzing petroleum reservoir.
Some commonly used methods for analyzing gene co-expression pattern in microarray data include hierarchical clustering [ 11], K-means clustering [ 12], and self organizing maps [ 13].
However, while simulation studies show that generalizing estimating equations have the greatest statistical power among several commonly used methods for analyzing binary clustered data, there are no guidelines that evaluated what method is the most appropriate; therefore, individual investigators will have to make judgments as to which analysis to conduct [ 26, 27].
HotSpotter offers a rapid, easy-to-use method for analyzing one's own and/or publicly available mutation data sets (as shown with the TCGA UCEC data set).
To meet this assumption, we used methods established for analyzing high-throughput functional genomic data sets (Rapaport et al., 2013).
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