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Bioinformatics Advance Access originally published online on July 26, 2006
Bioinformatics 2006 22(19):2444-2445; doi:10.1093/bioinformatics/btl408
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

ALIBABA: PubMed as a graph

Conrad Plake 1, Torsten Schiemann 1, Marcus Pankalla 2, Jörg Hakenberg 1,* and Ulf Leser 1

1 Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany
2 Department of Mathematics and Computer Science, Free University Berlin Arnimallee 2-6, 14195 Berlin, Germany

*To whom correspondence should be addressed.

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{at}informatik.hu-berlin.de

Received on April 28, 2006; revised on May 31, 2006; accepted on July 22, 2006

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