Medstract: creating large-scale information servers for biomedical libraries

  • Authors:

  • J. Pustejovsky;J. Castaño;R. Saurí;A. Rumshinsky;J. Zhang;W. Luo

  • Affiliations:

  • Brandeis University, Waltham, MA;Brandeis University, Waltham, MA;Brandeis University, Waltham, MA;Brandeis University, Waltham, MA;Brandeis University, Waltham, MA;Brandeis University, Waltham, MA

  • Venue:
  • BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
  • Year:
  • 2002

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Abstract

The automatic extraction of information from Medline articles and abstracts (commonly referred to now as the biobibliome) promises to play an increasingly critical role in aiding research while speeding up the discovery process. We have been developing robust natural language tools for the automated extraction of structured information from biomedical texts as part of a project we call MEDSTRACT. Here we will describe an architecture for developing databases for domain specific information servers for research and support in the biomedical community. These are currently comprised of the following: a Bio-Relation Server, and the Bio-Acronym server, Acromed, which will include also aliases. Each information server is derived automatically from an integration of diverse components which employ robust natural language processing of Medline text and IE techniques. The front-end consists of conventional search and navigation capabilities, as well as visualization tools that help to navigate the databases and explore the results of a search. It is hoped that this set of applications will allow for quick, structured access to relevant information on individual genes by biologists over the web.