PNNL

Abstract

With the completion of the Human Genome Project and the sequencing of large genomes, proteomics is the new big challenge. A proteome is the collection of all the proteins present in an organism at a given moment. Unlike the genome, the proteome is dynamic, changing continuously in response to tens of thousands of intra- and extra-cellular environmental signals. Proteomics is the study of proteomes under different conditions—for example, over time, under different environments, or in different disease states. Because proteins are the key actors in cellular processes and proteomics is the study of not one or two proteins at a time but whole proteomes, proteomics has a key role in revealing the complex processes of cells at a global or systems level. There are several high-throughput proteomics techniques; all generate data faster than the data can currently be analyzed. The tremendous size and complexity of the high-throughput experimental data make it very difficult to process and interpret. The success of proteomics will rely on high-throughput experimental techniques coupled with sophisticated visual analysis and data mining methods. This article presents the motivation for developing visual analysis tools for proteomic data and demonstrates their application to proteomics research with a visualization tool named Peptide Permutation and Protein Prediction, or PQuad. PQuad is a functioning visual analytic tool in operation at the Pacific Northwest National Laboratory for the study of systems biology. PQuad supports the exploration of proteins identified by proteomic techniques in the context of supplemental biological information.