PubNet: a flexible system for visualizing literature derived networks
1 Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
2 Department of Molecular Biology and Biochemistry, Center for Advanced Biotechnology and Medicine, Rutgers University and Robert Wood Johnson Medical School, Piscataway, NJ 08854, USA
3 Department of Computer Science, Yale University, New Haven, CT 06520, USA
Genome Biology 2005, 6:R80 doi:10.1186/gb-2005-6-9-r80Published: 16 August 2005
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.