Information Retrieval in Life Sciences: A Programmatic Survey

  • Matthias Lange
  • Ron Henkel
  • Wolfgang Müller
  • Dagmar Waltemath
  • Stephan Weise

Abstract

Biomedical databases are a major resource of knowledge for research in the life sciences. The biomedical knowledge is stored in a network of thousands of databases, repositories and ontologies. These data repositories differ substantially in granularity of data, storage formats, database systems, supported data models and interfaces. In order to make full use of available data resources, the high number of heterogeneous query methods and frontends requires high bioinformatic skills. Consequently, the manual inspection of database entries and citations is a time-consuming task for which methods from computer science should be applied.Concepts and algorithms from information retrieval (IR) play a central role in facing those challenges. While originally developed to manage and query less structured data, information retrieval techniques become increasingly important for the integration of life science data repositories and associated information. This chapter provides an overview of IR concepts and their current applications in life sciences. Enriched by a high number of selected references to pursuing literature, the following sections will successively build a practical guide for biologists and bioinformaticians.

Keywords

Information retrieval Data management Search engines Relevance ranking Recommender systems Semantic data networks Data integration 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Matthias Lange
    • 1
  • Ron Henkel
    • 2
  • Wolfgang Müller
    • 3
  • Dagmar Waltemath
    • 2
  • Stephan Weise
    • 1
  1. 1.Leibniz Institute of Plant Genetics and Crop Plant ResearchBioinformatics and Information TechnologyStadt SeelandGermany
  2. 2.Department of Systems Biology and BioinformaticsUniversity of RostockRostockGermany
  3. 3.HITS gGmbHHeidelbergGermany

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