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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arnau, V., Orduña, J.M., Ruiz, A., Duato, J.: On the Characterization of Interconnection Networks with Irregular Topology: a New Model of Communication Cost. In: Proceedings of the IASTED Internactonal Conference Parallel and Distributed Computing and Systems (PDCS 1999), Massachusetts, pp. 1–6 (1999)
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. John Wiley and Sons, Chichester (1973)
Everitt, B.: Cluster Analysis. John Wiley and Sons, New York (1974)
Fasulo, D.: An Analysis of Recent Works on Clustering Algorithms, Tech. Rep. # 01-03-02. Dpto. of Computer Science & Engineering, University of Washington (1999)
Gavin, A.-C., Bösche, M., Krause, R., Grandi, P., Marzioch, M., et al.: Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415, 141–147 (2002)
Ho, Y., Gruhler, A., Helibut, A., Bader, G.D., Moore, L., et al.: Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415, 180–183 (2002)
Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M., Sakaki, Y.: A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl. Acad. Sci. USA 98, 4569–4574 (2001)
Jeong, H., Mason, S.P., Barabási, A.-L., Oltvai, Z.N.: Lethality and centrality in protein networks. Nature 411, 41–42 (2001)
Nathanson, L., Deutscher, M.P.: Active aminoacyl-tRNA synthetases are present in nuclei as a high molecular weight multienzyme complex. J. Biol. Chem. 41, 31559–31562 (2000)
Orduña, J.M., Arnau, V., Duato, J.: Characterization of Communications between Processes in Message-Passing Applications. In: IEEE International Conference on Cluster Computing (CLUSTER2000), Chemnitz, Germany, pp. 91–98 (2000)
Rain, J.C., Selig, L., De Reuse, H., Battaglia, V., Reverdy, C., et al.: The protein-protein interaction map of Helicobacter pylori. Nature 409, 211–215 (2001)
Uetz, P., Giot, L., Cagney, G., Mansfield, T.A., Judson, R.S., et al.: A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature 403, 623–627 (2000)
von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S.G., Fields, S., Bork, P.: Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417, 399–403 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-540-44871-6_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40217-6
Online ISBN: 978-3-540-44871-6
eBook Packages: Springer Book Archive