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Experimental Diabetes Research
Volume 2008 (2008), Article ID 312060, 9 pages
http://dx.doi.org/10.1155/2008/312060
Methodology Report

GeneSpeed Beta Cell: An Online Genomics Data Repository and Analysis Resource Tailored for the Islet Cell Biologist

1Barbara Davis Center for Childhood Diabetes, University of Colorado, HSC., 1775 Ursula Street, B140, Aurora, CO 80045, USA
2Development and Physiopathology of the Intestine and Pancreas, Inserm-ULP Unit 682, 3 avenue Molière, Strasbourg 67200, France
3Lerner Research Institute, Department of Stem Cell and Regenerative medicine Cleveland Clinic, 9500 Euclid avenue, Cleveland, OH 44195, USA

Received 29 November 2007; Accepted 9 July 2008

Academic Editor: Ulf Eriksson

Copyright © 2008 Nayeem Quayum 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

Objective. We here describe the development of a freely available online database resource, GeneSpeed Beta Cell, which has been created for the pancreatic islet and pancreatic developmental biology investigator community. Research Design and Methods. We have developed GeneSpeed Beta Cell as a separate component of the GeneSpeed database, providing a genomics-type data repository of pancreas and islet-relevant datasets interlinked with the domain-oriented GeneSpeed database. Results. GeneSpeed Beta Cell allows the query of multiple published and unpublished select genomics datasets in a simultaneous fashion (multiexperiment viewing) and is capable of defining intersection results from precomputed analysis of such datasets (multidimensional querying). Combined with the protein-domain categorization/assembly toolbox provided by the GeneSpeed database, the user is able to define spatial expression constraints of select gene lists in a relatively rigid fashion within the pancreatic expression space. We provide several demonstration case studies of relevance to islet cell biology and development of the pancreas that provide novel insight into islet biology. Conclusions. The combination of an exhaustive domain-based compilation of the transcriptome with gene array data of interest to the islet biologist affords novel methods for multidimensional querying between individual datasets in a rapid fashion, presently not available elsewhere.