On Information Fusion in the Life-Sciences

  • Olaf Wolkenhauer
Part of the International Centre for Mechanical Sciences book series (CISM, volume 431)


In the present text, we shall discuss soft computing as concerned with the fusion of qualitative percepts and quantitative measurements. Whereas the former is obtained from observation, we shall assume that the latter is collected through measurements. Both, observation and measurement provide the information from which we derive knowledge in the modern life-sciences. Studying gene and/or protein interactions, biological databases are used to combine, for example, time-series measurements with sequence data and information about the classification of genes. These classifications or ‘annotations’ are the result of other experiments and observations, not necessarily linked to the experimental data investigated. The fusion of such context-dependent information with facts extracted from numerical data is of importance in the area of bioinformatics. The paper is to highlight the problems of information fusion in the life-sciences and outlines a conceptual framework in which to formulate such problems.


Fuzzy Cluster Information Fusion Evidence Theory Fuzzy Partition Fuzzy Equivalence Relation 
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-Verlag Wien 2001

Authors and Affiliations

  • Olaf Wolkenhauer
    • 1
  1. 1.Department of Biomolecular Sciences and Department of Electrical Engineering and ElectronicsControl Systems Centre UMISTManchesterUK

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