{"@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": ["009:25"], "contactPoint": {"@type": "vcard:Contact", "fn": "NIH", "hasEmail": "mailto:info@nih.gov"}, "description": "The lack of efficient techniques for assessing the biological implications of microarray gene-expression data remains an important obstacle in exploiting this information. To address this need, a mining technique has been developed based on the analysis of literature profiles generated by extracting the frequencies of certain terms from thousands of abstracts stored in the Medline literature database.", "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/PMC134484/", "mediaType": "text/html", "title": "Official Government Data Source"}], "identifier": "https://healthdata.gov/api/views/9qg9-prsr", "issued": "2025-07-14", "keyword": ["gene-expression", "literature-mining", "medline-abstracts", "microarray-data", "nih"], "landingPage": "https://healthdata.gov/d/9qg9-prsr", "modified": "2025-09-06", "programCode": ["009:033"], "publisher": {"@type": "org:Organization", "name": "National Institutes of Health"}, "theme": ["NIH"], "title": "Mining microarray expression data by literature profiling"}