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Graphle: Interactive exploration of large, dense graphs
Authors:Curtis Huttenhower  Sajid O Mehmood and Olga G Troyanskaya
Institution:(1) Department of Computer Science, Princeton University, Princeton, NJ 08540, USA;(2) Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA;(3) Current address: Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
Abstract:

Background  

A wide variety of biological data can be modeled as network structures, including experimental results (e.g. protein-protein interactions), computational predictions (e.g. functional interaction networks), or curated structures (e.g. the Gene Ontology). While several tools exist for visualizing large graphs at a global level or small graphs in detail, previous systems have generally not allowed interactive analysis of dense networks containing thousands of vertices at a level of detail useful for biologists. Investigators often wish to explore specific portions of such networks from a detailed, gene-specific perspective, and balancing this requirement with the networks' large size, complex structure, and rich metadata is a substantial computational challenge.
Keywords:
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