Using Pattern Structures for Analyzing Ontology-Based Annotations of Biomedical Data

  • Adrien Coulet
  • Florent Domenach
  • Mehdi Kaytoue
  • Amedeo Napoli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7880)


Annotating data with concepts of an ontology is a common practice in the biomedical domain. Resulting annotations, i.e., data-concept relationships, are useful for data integration whereas the reference ontology can guide the analysis of integrated data. Then the analysis of annotations can provide relevant knowledge units to consider for extracting and understanding possible correlations between data. Formal Concept Analysis (FCA) which builds from a binary context a concept lattice can be used for such a knowledge discovery task. However annotated biomedical data are usually not binary and a scaling procedure for using FCA is required as a preprocessing, leading to problems of expressivity, ranging from loss of information to the generation of a large number of additional binary attributes. By contrast, pattern structures offer a general FCA-based framework for building a concept lattice from complex data, e.g., a set of objects with partially ordered descriptions. In this paper, we show how to instantiate this general framework when descriptions are ordered by an ontology. We illustrate our approach with the analysis of annotations of drug related documents, and we show the capabilities of the approach for knowledge discovery.


Hull Streptomycin MeSH 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Adrien Coulet
    • 1
  • Florent Domenach
    • 2
  • Mehdi Kaytoue
    • 3
  • Amedeo Napoli
    • 1
  1. 1.LORIA (Université de Lorraine – CNRS – Inria Nancy Grand Est, UMR 7503)Vandoeuvre-lès-NancyFrance
  2. 2.Computer Science DepartmentUniversity of NicosiaNicosiaCyprus
  3. 3.CNRS, INSA-Lyon, LIRIS, UMR5205Université de LyonFrance

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