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Statistical Analysis Gene Expression refers to the application of statistical methods and models to analyze gene expression data. This field is integral to bioinformatics, a discipline that employs computational tools and approaches to understand biological data. In this context, Statistical Analysis Gene Expression involves examining large-scale gene expression datasets generated through techniques such as microarray analysis or RNA sequencing. Researchers utilize statistical models to identify differentially expressed genes, detect patterns and correlations, and make predictions about gene function or regulation. This subcategory is closely related to genetics, where it aids in the interpretation of genetic data and the identification of genotype-phenotype relationships. In the broader context of science, Statistical Analysis Gene Expression contributes to our understanding of biological systems, disease mechanisms, and evolutionary processes.