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Knowledge Acquisition from the Biomedical Literature

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Semantic Web

Abstract

This article focuses on knowledge acquisition from the biomedical literature, and on the infrastructure, specifically text mining, needed to access, extract and integrate the information. The biomedical literature is the major repository of biomedical knowledge. It serves as the source for structured information that populates biological databases, via the process of expert distillation (or curation) of the literature. Today, the literature has grown to the point where an individual scientist cannot read all the relevant literature, and curators of the major biological databases have trouble keeping up to date with newly published articles. Furthermore, important biomedical applications, such as drug discovery and analysis of high-throughput data sets, are dependent on integration of all available information from both biological databases and the literature. The article reviews these applications, focusing on the role of text mining in providing semantic indices into the literature, as well as the importance of interactive tools to augment the power of the human expert to extract information from the literature. These tools are critical in supporting expert curation, finding relationships among biological entities, and creating content for a Semantic Web.

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Author information

Authors and Affiliations

  1. The MITRE Corporation, USA

    Lynette Hirschman

  2. Biogen Idec, USA

    William S. Hayes

  3. Spanish National Cancer Research Centre, Spain

    Alfonso Valencia

Authors
  1. Lynette Hirschman
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  2. William S. Hayes
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  3. Alfonso Valencia
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Editor information

Editors and Affiliations

  1. Knowledge Discovery Department, Institute for Infocomm Research, Singapore

    Christopher J. O. Baker

  2. Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA

    Kei-Hoi Cheung

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Hirschman, L., Hayes, W.S., Valencia, A. (2007). Knowledge Acquisition from the Biomedical Literature. In: Baker, C.J.O., Cheung, KH. (eds) Semantic Web. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-48438-9_4

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