We visualize gene co-regulation patterns by creating 2D embeddings from microarray data corresponding to complete gene sets from the mouse genome, across large numbers of cell types. We use google maps and client-side graphics to disseminate pre-rendered such visualizations with a small but intuitive set of interactions. We conduct an anecdotal evaluation with domain specialists and demonstrate that biologists appreciate this approach because it facilitates low-overhead access to readily analyzable perspectives of unfamiliar datasets and because it offers a convenient way of disseminating large datasets in visual form. © 2010 Springer-Verlag.
CITATION STYLE
Jianu, R., & Laidlaw, D. H. (2010). Visualizing gene co-expression as google maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6455 LNCS, pp. 494–503). https://doi.org/10.1007/978-3-642-17277-9_51
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