title: Proteomic Clustering Analysis of SH2 Domain Datasets.
abstract: 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.
authors.affiliation: Division of Emergency Medicine, Department of Medicine, University of Washington, 325 9th Ave., Seattle, WA, USA. kdj6@uw.edu.|Division of Biomedical and Health Informatics, Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA. kdj6@uw.edu.
authors.forename: Karl
authors.initials: K
authors.lastname: Jablonowski
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D019143:Evolution, Molecular; D006801:Humans; D008024:Ligands; D010802:Phylogeny; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D040901:Proteomics / Q000379:methods*; D012984:Software; D018909:src Homology Domains
chemical_list: D008024:Ligands
keywords: Euclidean distance; Evolutionary analysis; Neighbor-joining phylogenetic tree; Peptide ligand binding pattern