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An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology

Supporting Files Public Domain


Details

  • Alternative Title:
    BMC Bioinformatics
  • Personal Author:
  • Description:
    Background ; Identifying relevant research in an ever-growing body of published literature is becoming increasingly difficult. Establishing domain-specific knowledge bases may be a more effective and efficient way to manage and query information within specific biomedical fields. Adopting controlled vocabulary is a critical step toward data integration and interoperability in any information system. We present an open source infrastructure that provides a powerful capacity for managing and mining data within a domain-specific knowledge base. As a practical application of our infrastructure, we presented two applications – Literature Finder and Investigator Browser – as well as a tool set for automating the data curating process for the human genome published literature database. The design of this infrastructure makes the system potentially extensible to other data sources. ; Results ; Information retrieval and usability tests demonstrated that the system had high rates of recall and precision, 90% and 93% respectively. The system was easy to learn, easy to use, reasonably speedy and effective. ; Conclusion ; The open source system infrastructure presented in this paper provides a novel approach to managing and querying information and knowledge from domain-specific PubMed data. Using the controlled vocabulary UMLS enhanced data integration and interoperability and the extensibility of the system. In addition, by using MVC-based design and Java as a platform-independent programming language, this system provides a potential infrastructure for any domain-specific knowledge base in the biomedical field.
  • Subjects:
  • Source:
    BMC Bioinformatics. 2007; 8:436.
  • Document Type:
  • Volume:
    8
  • Download URL:
  • File Type:
    Filetype[PDF - 813.97 KB]
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:9dc4dbee4345b6575a78fde9cd45197bde831bccb6e0a68a512ef038340bb5aee058265edf7508bcefaad287897ef8c30aececc25e8f11f9cf66fd4053e0b309
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