Rodrigo Santamaría1, Philippe Pierre. 1. Departmento de Informática y Automática, Universidad de Salamanca, 37008 Salamanca, Spain. rodri@usal.es
Abstract
MOTIVATION: Several techniques analyze gene expression data from the point of view of biological ontologies. These methods focus on statistical and numerical analyses, but there is an additional need for fast, global and interactive visualizations of gene expression data in the context of biological ontologies. RESULTS: Voronto addresses these needs with an easy to use integration of custom gene expression data with custom or public ontologies. In order to do that, it implements Voronoi diagrams where ontologies are mapped with gene expression, providing a quick hierarchy browsing and integration with ontology's resources. AVAILABILITY: The tool is available at http://vis.usal.es/voronto. Source code available at https:/github.com/rodrigoSantamaria/Voronto.
MOTIVATION: Several techniques analyze gene expression data from the point of view of biological ontologies. These methods focus on statistical and numerical analyses, but there is an additional need for fast, global and interactive visualizations of gene expression data in the context of biological ontologies. RESULTS: Voronto addresses these needs with an easy to use integration of custom gene expression data with custom or public ontologies. In order to do that, it implements Voronoi diagrams where ontologies are mapped with gene expression, providing a quick hierarchy browsing and integration with ontology's resources. AVAILABILITY: The tool is available at http://vis.usal.es/voronto. Source code available at https:/github.com/rodrigoSantamaria/Voronto.
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