We have developed PubNet, a web-based tool that extracts several types of relationships returned by PubMed queries and maps them into networks, allowing for graphical visualization, textual navigation, and topological analysis. PubNet supports the creation of complex networks derived from the contents of individual citations, such as genes, proteins, Protein Data Bank (PDB) IDs, Medical Subject Headings (MeSH) terms, and authors. This feature allows one to, for example, examine a literature derived network of genes based on functional similarity.
I've added it to my Connotea library under the tag visualisation (note to self: American English and British English spelling is just one of the problems with "tagging"). I'd seen this paper before, but "forgot" it until browsing Connotea and stumbling across nicmila's library. Nice illustration of the power of shared tags.
(Via nicmila.)
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