Cambridge Healthtech Institute, The Hyatt Regency on Capital Hill
August 24-26, 2005
Microarrays are costly - both in time and resources - making the careful design of microarray experiments to generate good data for diagnostics, target identification, screening, genotyping and other applications critical. Statistical analysis of data generated from well-designed experiments allows for meaningful biological correlation. To generate such statistically defensible data requires effective communication between those designing and running the experiments, and those doing data analysis in conjunction with software database developers who facilitate data handling. CHI's 5th Annual Total Microarray Data Analysis and Interpretation brings together these three groups to explore how useful microarray data should be generated, stored, mined, and interpreted to answer the questions being asked.
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