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Abstract
GenoSIS: Genome Data Interpretation Using GIS
Track: Modeling
Author(s): Mary Dolan, Constance Holden, M. Beard, Carol Bult
Advances in DNA sequencing have resulted in data generation that has far outpaced the available visualization and analysis tools needed for efficient interpretation of this data. To understand the biological significance and interconnectedness of this data, the Jackson Laboratory developed the Genome Spatial Information System (GenoSIS) as an application of the concepts and tools of geographic and spatial information science for the interpretation and modeling of genome data. The implementation of "spatial genomics," which uses Esri ArcGIS and Oracle Spatial, allows the reuse of existing spatial analysis, classification, query, and visualization tools for genome data analysis.
Mary Dolan
The Jackson Laboratory
NCGIA, National Center for Geographic Information and Analysis
University of Maine
Boardman Hall 329
Orono , ME 04469
USA
Phone: (207)581-2143
Fax: (207)581-2206
E-mail: mary_dolan@umit.maine.edu
Constance Holden
NCGIA, National Center for Geographic Information and Analysis
Spatial Information Science and Engineering
University of Maine
Boardman Hall 125
Orono 04469
USA
Phone: (207)581-3952
Fax: (207)581-2206
E-mail: cholden@spatial.maine.edu
M. Beard
NCGIA, National Center for Geographic Information and Analysis
Spatial Information Science and Engineering
University of Maine
Boardman Hall 348A
Orono 04469
USA
Phone: (207)581-2147
Fax: (207)581-2206
E-mail: beard@spatial.maine.edu
Carol Bult
The Jackson Laboratory
NCGIA, National Center for Geographic Information and Analysis
600 Main Street
Bar Harbor , Maine 04609 Phone: (207)288-6324
Fax: (207)581-2206
E-mail: cjb@informatics.jax.org