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Data Mining in situ Gene Expression Patterns at Cellular Resolution
Stanford, California August 08-August 11
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSBW.2005.492005 IEEE Computational Systems Bioin ...
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James Carson, National Center for Macromolecular Imaging
Tao Ju, Dept. of Computer Science, Rice University, Houston TX.
Christina Thaller, Biochemistry and Molecular Biology, Baylor College of Medicine
M. Bello, Dept. of Computer Science, University of Houston
Joe Warren, Dept. of Computer Science, Rice University, Houston TX.
Gregor Eichele, Max Planck Institute of Experimental Endocrinology, Hannover, Germany
Wah Chiu, Biochemistry and Molecular Biology, Baylor College of Medicine

Non-radioactive in situ hybridization (ISH) is a powerful technique for revealing gene expression in individual cells, the level of detail necessary for investigating how genes control cell type identity, cell differentiation, and cell-cell signaling. Although the availability of robotic ISH enables the expeditious determination of expression patterns for thousands of genes in serially sectioned tissues, a large collection of ISH images is, per se, of limited benefit. However, via accurate detection of expression strength and spatial normalization of expression location across different specimens, ISH images become a minable resource of annotated gene expression capable of advancing functional genomics in a mode similar to DNA sequence databases. We have developed

Citation:
James Carson, Tao Ju, Christina Thaller, M. Bello, Joe Warren, Gregor Eichele, Wah Chiu, "Data Mining in situ Gene Expression Patterns at Cellular Resolution," csbw, pp.358, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2005
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