Browsing Research Institute of Biosensors Technology by Author "Cantini, Laura"

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Determining the optimal number of independent components for reproducible transcriptomic data analysis

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei (BioMed Central, 2017)

Background: Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the ...