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Issue No. 01 - January-March (2010 vol. 7)
ISSN: 1545-5963
pp: 12-24
Carol Lushbough , University of South Dakota, Vermillion
Michael K. Bergman , VisualMetrics Corporation, Coralville
Carolyn J. Lawrence , USDA-ARS Iowa State University, Ames
Doug Jennewein , University of South Dakota, Vermillion
Volker Brendel , Iowa State University, Ames
Many in silico investigations in bioinformatics require access to multiple, distributed data sources and analytic tools. The requisite data sources may include large public data repositories, community databases, and project databases for use in domain-specific research. Different data sources frequently utilize distinct query languages and return results in unique formats, and therefore researchers must either rely upon a small number of primary data sources or become familiar with multiple query languages and formats. Similarly, the associated analytic tools often require specific input formats and produce unique outputs which make it difficult to utilize the output from one tool as input to another. The BioExtract Server ( is a Web-based data integration application designed to consolidate, analyze, and serve data from heterogeneous biomolecular databases in the form of a mash-up. The basic operations of the BioExtract Server allow researchers, via their Web browsers, to specify data sources, flexibly query data sources, apply analytic tools, download result sets, and store query results for later reuse. As a researcher works with the system, their “steps” are saved in the background. At any time, these steps can be preserved long-term as a workflow simply by providing a workflow name and description.
Bioinformatics (genome or protein) databases, data integration, distributed architectures, heterogeneous databases, mash-up, scientific workflow automation.

C. J. Lawrence, D. Jennewein, M. K. Bergman, V. Brendel and C. Lushbough, "BioExtract Server—An Integrated Workflow-Enabling System to Access and Analyze Heterogeneous, Distributed Biomolecular Data," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. , pp. 12-24, 2008.
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