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                                             BIOINFORMATICS COLLOQUIUM
						College of Science
                                              George Mason University
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                      Biological Pathway and Network Analysis for Functional Interpretation of 
                                              Large-Scale Omics Data

						 
                                                   Zhang-Zhi Hu

   				              Georgetown University

Abstract:
The last decade has seen rapid expansion of genomics, transcriptomics, proteomics and other 
"-omics" as applied to biomedical researches. However, making senses out of the deluge of omics 
data remains challenging and requires effective bioinformatics approaches for data integration, 
analyses, and interpretation, which has become an active area of bioinformatics research, and is 
crucial to the realization of full potentials that omics are hoped to bring. We took a protein-centric 
data integration and analysis approach and developed iProXpress bioinformatics system 
(http://pir.georgetown.edu/iproxpress/) for functional analysis of large-scale data, primarily from 
gene expression and proteomics studies. The system contains three major components: a data warehouse 
with information derived from over 90 databases, analytical tools for sequence analysis and functional 
annotation, and a graphical user interface for iterative and comparative function and pathway analysis. 
The system's unique features include its comprehensiveness of protein sequence coverage and annotation, 
high protein mapping rate of expression data including protein spliced forms, and its versatility of 
use on different types of omics data. We applied this approach to several cancer studies for 
identifying pathways and networks, including organelle biogenesis in melanocytes, signaling and metabolic 
pathways in hormone- or radiation-resistant breast cancer and other cells. Our studies highlight the need 
of functional profiling, pathway/network analysis coupled with expert-guided examination for omics data 
interpretation and for hypothesis formulation.