Text Mining for Systems Modeling

  • Axel Kowald
  • Sebastian Schmeier
Part of the Methods in Molecular Biology book series (MIMB, volume 696)


The yearly output of scientific papers is constantly rising and makes it often impossible for the individual researcher to keep up. Text mining of scientific publications is, therefore, an interesting method to automate knowledge and data retrieval from the literature. In this chapter, we discuss specific tasks required for text mining, including their problems and limitations. The second half of the chapter demonstrates the various aspects of text mining using a practical example. Publications are transformed into a vector space representation and then support vector machines are used to classify papers depending on their content of kinetic parameters, which are required for model building in systems biology.


Support Vector Machine Text Mining Receiver Operator Curve Biological Entity Vector Space Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Axel Kowald
    • 1
  • Sebastian Schmeier
    • 2
  1. 1.Protagen AGDortmundGermany
  2. 2.South African National Bioinformatics InstituteUniversity of the Western CapeBellvilleSouth Africa

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