{"@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": ["009:25"], "contactPoint": {"@type": "vcard:Contact", "fn": "NIH", "hasEmail": "mailto:info@nih.gov"}, "description": "Background\n          Microarray technologies are emerging as a promising tool for genomic studies. The challenge now is how to analyze the resulting large amounts of data. Clustering techniques have been widely applied in analyzing microarray gene-expression data. However, normal mixture model-based cluster analysis has not been widely used for such data, although it has a solid probabilistic foundation. Here, we introduce and illustrate its use in detecting differentially expressed genes. In particular, we do not cluster gene-expression patterns but a summary statistic, the t-statistic.\n        \n        \n          Results\n          The method is applied to a data set containing expression levels of 1,176 genes of rats with and without pneumococcal middle-ear infection. Three clusters were found, two of which contain more than 95% genes with almost no altered gene-expression levels, whereas the third one has 30 genes with more or less differential gene-expression levels.\n        \n        \n          Conclusions\n          Our results indicate that model-based clustering of t-statistics (and possibly other summary statistics) can be a useful statistical tool to exploit differential gene expression for microarray data.", "distribution": [{"@type": "dcat:Distribution", "description": "Visit the original government dataset for complete information, documentation, and data access.", "downloadURL": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC65687/", "mediaType": "text/html", "title": "Official Government Data Source"}], "identifier": "https://healthdata.gov/api/views/yh42-xkaf", "issued": "2025-07-14", "keyword": ["cluster-analysis", "gene-expression", "microarray-data", "nih", "pneumococcal-infection"], "landingPage": "https://healthdata.gov/d/yh42-xkaf", "modified": "2025-09-06", "programCode": ["009:033"], "publisher": {"@type": "org:Organization", "name": "National Institutes of Health"}, "theme": ["NIH"], "title": "Model-based cluster analysis of microarray gene-expression data"}