Abstract
BackgroundPublic databases are crucial for analysis of high-dimensional gene and protein expression data. The Urologic Epithelial Stem Cells (UESC) database is a public database that contains gene and protein information for the major cell types of the prostate, prostate cancer cell lines, and a cancer cell type isolated from a primary tumor. Similarly, such information is available for urinary bladder cell types.DescriptionTwo major data types were archived in the database, protein abundance localization data from immunohistochemistry images, and transcript abundance data principally from DNA microarray analysis. Data results were organized in modules that were made to operate independently but built upon a core functionality. Gene array data and immunostaining images for human and mouse prostate and bladder were made available for interrogation. Data analysis capabilities include: (1) CD (cluster designation) cell surface protein data. For each cluster designation molecule, a data summary allows easy retrieval of images (at multiple magnifications). (2) Microarray data. Single gene or batch search can be initiated with Affymetrix Probeset ID, Gene Name, or Accession Number together with options of coalescing probesets and/or replicates.ConclusionDatabases are invaluable for biomedical research, and their utility depends on data quality and user friendliness. UESC provides for database queries and tools to examine cell type-specific gene expression (normal vs. cancer), whereas most other databases contain only whole tissue expression datasets. The UESC database provides a valuable tool in the analysis of differential gene expression in prostate cancer genes in cancer progression.
Highlights
Public databases are crucial for analysis of high-dimensional gene and protein expression data
Databases are invaluable for biomedical research, and their utility depends on data quality and user friendliness
Urologic Epithelial Stem Cells (UESC) provides for database queries and tools to examine cell typespecific gene expression, whereas most other databases contain only whole tissue expression datasets
Summary
Strategies for the analysis of the interface between gene expression and protein information involve a variety of computational methods that require the storage and retrieval of large datasets. These databases become perforce an integral component of biomedical research. Http://www.biomedcentral.com/1471-2490/7/19 tion and characterization of genes and proteins in specific cell types of the urologic organs where cancer is a major disease These cell populations retain to a high degree their CD phenotype as determined by immunostaining in intact tissue; concordance between gene expression measured by DNA array and immunohistochemistry was good and will be published separately. MISFISHIE: Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments
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