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AliBaba: PubMed as a graph
Conrad Plake1, Torsten Schiemann, Marcus Pankalla
1Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany.
Unlabelled:
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/
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