Lab-on-a-Chip

Level III is for users who wish to master advanced data analysis by making more informed algorithm choices. This course covers the theory and application of self-organizing maps, k-means and QT clustering, as well as associated similarity metrics. You will also learn about the class prediction tool and how to use this supervised learning method to predict the identity of unknown samples. Other advanced methods, such as finding potential regulatory sequences based on shared expression patterns, and cross-referencing results between data from different organisms, will also be covered.

The pace of the workshop assumes users are very comfortable navigating through menus, graphical interface, and know the basics of data analysis. Users should have worked with multiple data sets in GeneSpring. Users should have attended the DNA Microarray Level II Workshop (R1796A) or attended the following eSeminar:"Basic Statistics for GeneSpring".