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A Hierarchical Clustering Strategy and Its Application to Proteomic Interaction Data

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Pattern Recognition and Image Analysis (IbPRIA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2652))

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Abstract

We describe a novel strategy of hierarchical clustering analysis, particularly useful to analyze proteomic interaction data. The logic behind this method is to use the information for all interactions among the elements of a set to evaluate the strength of the interaction of each pair of elements. Our procedure allows the characterization of protein complexes starting with partial data and the detection of "promiscuous" proteins that bias the results, generating false positive data. We demonstrate the usefulness of our strategy by analyzing a real case that involves 137 Saccharomyces cerevisiae proteins. Because most functional studies require the evaluation of similar data sets, our method has a wide range of applications and thus it can be established as a benchmark analysis for proteomic data.

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Authors and Affiliations

  1. Departamento de Informática, Universidad de Valencia, Campus de Burjassot, Avda. Vicent Andrés Estellés, s/n., 46100, Burjassot, Valencia, Spain

    Vicente Arnau

  2. Departamento de Genética, Universidad de Valencia, Campus de Burjassot, Calle Doctor Moliner, 50., 46100, Burjassot, Valencia, Spain

    Ignacio Marín

Authors
  1. Vicente Arnau
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  2. Ignacio Marín
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Editors and Affiliations

  1. Unitat de Gràfics i Visió per Ordinador Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears Edifici Anselm Turmeda, Ctra. de Valldemossa km 7,5, 07122, Palma de Mallorca, Spain

    Francisco José Perales

  2. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio J. C. Campilho

  3. Departamento de Ciencias da la Computacíon e I.A., Universidad de Granada, E.T. S. Ing. Informática, 18071, Granada, Spain

    Nicolás Pérez de la Blanca

  4. Dept. System Engineering and Automation, Universitat Politècnica de Catalunya (UPC) Barcelona, Spain

    Alberto Sanfeliu

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© 2003 Springer-Verlag Berlin Heidelberg

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Arnau, V., Marín, I. (2003). A Hierarchical Clustering Strategy and Its Application to Proteomic Interaction Data. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_8

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  • DOI: https://doi.org/10.1007/978-3-540-44871-6_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40217-6

  • Online ISBN: 978-3-540-44871-6

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