title: AliBaba: PubMed as a graph.
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.
  
  
  BACKGROUND
  http://alibaba.informatik.hu-berlin.de/
authors.affiliation: Knowledge Management in Bioinformatics, Humboldt-Universität zu Berlin Unter den Linden 6, 10099 Berlin, Germany.
authors.forename: Conrad
authors.initials: C
authors.lastname: Plake
authors.forename: Torsten
authors.initials: T
authors.lastname: Schiemann
authors.forename: Marcus
authors.initials: M
authors.lastname: Pankalla
authors.forename: Jörg
authors.initials: J
authors.lastname: Hakenberg
authors.forename: Ulf
authors.initials: U
authors.lastname: Leser
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods*; D000465:Algorithms; D003196:Computer Graphics; D003628:Database Management Systems; D016247:Information Storage and Retrieval / Q000379:methods; D009323:Natural Language Processing; D010506:Periodicals as Topic; D012984:Software; D014584:User-Computer Interface; D018875:Vocabulary, Controlled