Archive for May, 2016

Imputation of Missing Values in Clinical Research

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Currently, the pharmaceutical and scientific communities are highly interested in the functional role of “-omics” data in clinical research. Omics data (e.g. DNA, mRNA, microRNA) help to understand pathways and biological processes along with identifying genetic variation or differentially expressed genes as potential biomarkers for drug target discovery and patient stratification. Omics data, particularly gene expression data, often contain missing values. This missingness often occurs due to insufficient resolution, image corruption, dust or scratches on the slide, other various experimental and technical reasons or even may happen due to lack of collected tissue or limited funds. Many statistical methods for…

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