This network graph was automatically generated by botXminer, a publicly available, Web-based application to search XML-formatted data of The National Library of Medicine's (NLM) MEDLINE/PubMed biomedical literature database in a complete, object-relational schema implemented in Oracle XML DB.

An advantage offered by botXminer is that it can generate quantitative results with certain queries that are not feasible through the Entrez-PubMed interface. After retrieving citations associated with user-supplied search terms, MEDLINE fields (title, abstract, journal, MeSH and chemical) and terms (MeSH qualifiers and descriptors, keywords, author, gene symbol and chemical), these citations are grouped and displayed as tabulated or graphic results. The visualization is done with the aid of aiSee.

The above interconnectedness graph shows the relationships between pairs of chemical terms. The terms are linked to references (color-coded lines) with the number of co-occurrences labeled in the small circles. The lines and circles are color-coded depending on the number of articles: gray for terms that co-occur in 1 article, yellow for co-occurrence in 2—5 articles, pink for 6—10 articles and green for >10 articles.

» Free trial: botXminer home page
» Free white paper: mining biomedical literature with botXminer

» Related app: PubNet
» Related app: Chilibot
» Related app: GeneIlluminator
» See also: Co-authorship graphs
» More from aiSee users in the US

Last modified on 9 August 2006 by webmaster. © 2006 AbsInt.
Graph © SAIC-Frederick, Inc., USAMRIID and Oxford University Press.
URL: http://www.aisee.com/graph_of_the_month/botxm.htm

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