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Advances in Bioinformatics
Volume 2010, Article ID 423589, 19 pages
http://dx.doi.org/10.1155/2010/423589
Review Article

Protein Bioinformatics Infrastructure for the Integration and Analysis of Multiple High-Throughput “omics” Data

1Department of Computer & Information Sciences, Center for Bioinformatics & Computational Biology, University of Delaware, Newark, DE 19711, USA
2Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA

Received 4 October 2009; Accepted 5 January 2010

Academic Editor: Huixiao Hong

Copyright © 2010 Chuming Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

High-throughput “omics” technologies bring new opportunities for biological and biomedical researchers to ask complex questions and gain new scientific insights. However, the voluminous, complex, and context-dependent data being maintained in heterogeneous and distributed environments plus the lack of well-defined data standard and standardized nomenclature imposes a major challenge which requires advanced computational methods and bioinformatics infrastructures for integration, mining, visualization, and comparative analysis to facilitate data-driven hypothesis generation and biological knowledge discovery. In this paper, we present the challenges in high-throughput “omics” data integration and analysis, introduce a protein-centric approach for systems integration of large and heterogeneous high-throughput “omics” data including microarray, mass spectrometry, protein sequence, protein structure, and protein interaction data, and use scientific case study to illustrate how one can use varied “omics” data from different laboratories to make useful connections that could lead to new biological knowledge.