title: PubNet: a flexible system for visualizing literature derived networks.
abstract: 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.
authors.affiliation: Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA. sdouglas@fas.harvard.edu
authors.forename: Shawn M
authors.initials: SM
authors.lastname: Douglas
authors.forename: Gaetano T
authors.initials: GT
authors.lastname: Montelione
authors.forename: Mark
authors.initials: M
authors.lastname: Gerstein
mesh_terms: D016206:Databases, Bibliographic; D030562:Databases, Protein; D020407:Internet; D008091:Literature; D046650:Medical Subject Headings; D010506:Periodicals as Topic; D012106:Research; D012984:Software