Cluster analysis of protein array results via similarity of Gene Ontology annotation

Background: With the advent of high-throughput proteomic experiments such as arrays of purified proteins comes the need to analyse sets of proteins as an ensemble, as opposed to the traditional one-protein-at-a-time approach. Although there are several publicly available tools that facilitate the analysis of protein sets, they do not display integrated results in an easily-interpreted image or do not allow the user to specify the proteins to be analysed. Results: We developed a novel computational approach to analyse the annotation of sets of molecules. As proof of principle, we analysed two sets of proteins identified in published protein array screens. The distance between any two proteins was measured as the graph similarity between their Gene Ontology (GO) annotations. These distances were then clustered to highlight subsets of proteins sharing related GO annotation. In the first set of proteins found to bind small molecule inhibitors of rapamycin, we identified three subsets cont...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Cheryl Wolting, C. Jane McGlade, David Tritchler
• Keywords: Annotations, BMCBI 2006, Proteins, Traditional One-protein-at-a-time Approach