AliBaba: PubMed as a graph

Authors:
Conrad Plake;Torsten Schiemann;Marcus Pankalla;Jörg Hakenberg;Ulf Leser
Affiliations:
Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany;Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany;Department of Mathematics and Computer Science, Free University Berlin Arnimallee 2-6, 14195 Berlin, Germany;Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany;Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany
Venue:
Bioinformatics
Year:
2006

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Abstract

The biomedical literature contains a wealth of information on associations between many different types of objects, such as protein--protein interactions, gene--disease associations and subcellular locations of proteins. When searching such information using conventional search engines, e.g. PubMed, users see the data only one-abstract at a time and 'hidden' in natural language text. AliBaba is an interactive tool for graphical summarization of search results. It parses the set of abstracts that fit a PubMed query and presents extracted information on biomedical objects and their relationships as a graphical network. AliBaba extracts associations between cells, diseases, drugs, proteins, species and tissues. Several filter options allow for a more focused search. Thus, researchers can grasp complex networks described in various articles at a glance. Availability: http://alibaba.informatik.hu-berlin.de/ Contact: hakenberg@informatik.hu-berlin.de