LAUSR

Proteomic clustering analysis provides a means of identifying relationships and visualizing those relationships in an extremely complex field of study with many interacting parts. With recent high-throughput studies of Src Homology 2 (SH2) domains, many and varied datasets are being amassed. A strategy for analyzing patterns between these large datasets is required to transform the information into knowledge. The methods for creating neighbor-joining phylogenetic trees, pairs scatter plots, and two-dimensional hierarchical clustering heatmaps are just a few of the diverse methods available to a proteomic researcher. This chapter examines selecting objects to be analyzed, selecting comparison functions to apply to those objects, and pseudo-code for processing data and preparing it for various types of analyses. Here I apply clustering analysis to previous collections of SH2 domains datasets to bring insight into new binding or specificity patterns between the different SH2 domains.