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AliBaba: PubMed as a graph.

Conrad Plake·Torsten Schiemann·Marcus Pankalla·Jörg Hakenberg·Ulf Leser
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Abstract

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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Abstracting and IndexingAlgorithmsComputer GraphicsDatabase Management SystemsInformation Storage and RetrievalNatural Language ProcessingPeriodicals as TopicSoftwareUser-Computer InterfaceVocabulary, ControlledJournal ArticleResearch Support, Non-U.S. Gov't

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Conrad Plake, Torsten Schiemann, Marcus Pankalla, Jörg Hakenberg, Ulf Leser. 2006-07-26. AliBaba: PubMed as a graph.. https://doi.org/10.1093/bioinformatics%2Fbtl408

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