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Association Analysis Techniques for Bioinformatics Problems

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Bioinformatics and Computational Biology (BICoB 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5462))

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Abstract

Association analysis is one of the most popular analysis paradigms in data mining. Despite the solid foundation of association analysis and its potential applications, this group of techniques is not as widely used as classification and clustering, especially in the domain of bioinformatics and computational biology. In this paper, we present different types of association patterns and discuss some of their applications in bioinformatics. We present a case study showing the usefulness of association analysis-based techniques for pre-processing protein interaction networks for the task of protein function prediction. Finally, we discuss some of the challenges that need to be addressed to make association analysis-based techniques more applicable for a number of interesting problems in bioinformatics.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Minnesota, USA

    Gowtham Atluri, Rohit Gupta, Gang Fang, Gaurav Pandey, Michael Steinbach & Vipin Kumar

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  1. Gowtham Atluri
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  2. Rohit Gupta
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  3. Gang Fang
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  4. Gaurav Pandey
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  5. Michael Steinbach
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  6. Vipin Kumar
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Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Connecticut, 257 ITE Building, 371 Fairfield Way, CT 06269-2155, Storrs, USA

    Sanguthevar Rajasekaran

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Atluri, G., Gupta, R., Fang, G., Pandey, G., Steinbach, M., Kumar, V. (2009). Association Analysis Techniques for Bioinformatics Problems. In: Rajasekaran, S. (eds) Bioinformatics and Computational Biology. BICoB 2009. Lecture Notes in Computer Science(), vol 5462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00727-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-00727-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

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