PubNet: a flexible system for visualizing literature derived networks

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.

• Publication year

  2005

• Venue

  Genome Biology

• Publication date

  2005-08-16

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1186/gb-2005-6-9-r80PMID 16168087PMCID 1242215
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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