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Towards an Integrated Protein-Protein Interaction Network

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Research in Computational Molecular Biology (RECOMB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3500))

Abstract

Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is of great importance, and has been addressed both experimentally and computationally. Today, large scale experimental studies of interacting proteins, while partial and noisy, allow us to characterize properties of interacting proteins and develop predictive algorithms. Most existing algorithms, however, ignore possible dependencies between interacting pairs, and predict them independently of one another. In this study, we present a computational approach that overcomes this drawback by predicting protein-protein interactions simultaneously. In addition, our approach allows us to integrate various protein attributes and explicitly account for uncertainty of assay measurements. Using the language of relational Markov Random Fields, we build a unified probabilistic model that includes all of these elements. We show how we can learn our model properties efficiently and then use it to predict all unobserved interactions simultaneously. Our results show that by modeling dependencies between interactions, as well as by taking into account protein attributes and measurement noise, we achieve a more accurate description of the protein interaction network. Furthermore, our approach allows us to gain new insights into the properties of interacting proteins.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel

    Ariel Jaimovich & Nir Friedman

  2. Hadassah Medical School, The Hebrew University, Jerusalem, Israel

    Ariel Jaimovich & Hanah Margalit

  3. Computer Science Department, Stanford University, Stanford, California, USA

    Gal Elidan

Authors
  1. Ariel Jaimovich
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  2. Gal Elidan
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  3. Hanah Margalit
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  4. Nir Friedman
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Editor information

Editors and Affiliations

  1. Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, 108-8639, Minato-ku, Tokyo, Japan

    Satoru Miyano

  2. Broad Institute of MIT and Harvard, 320 Charles Street, 02141-2023, Cambridge, MA, USA

    Jill Mesirov

  3. Computational Genomics Laboratory, Department of Bioengineering, Boston University, 44 Cummington St., 02215, Boston, MA, USA

    Simon Kasif

  4. Center for Molecular Biology and Computer Sciecne Department, Brown University, 115 Waterman St., 02912, Providence, RI, USA

    Sorin Istrail

  5. University of California, San Diego, USA

    Pavel A. Pevzner

  6. Department of Molecular and Computational Biology, University of Southern California, 1050 Childs Way, 90089-2910, Los Angeles, CA, USA

    Michael Waterman

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© 2005 Springer-Verlag Berlin Heidelberg

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Jaimovich, A., Elidan, G., Margalit, H., Friedman, N. (2005). Towards an Integrated Protein-Protein Interaction Network. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2005. Lecture Notes in Computer Science(), vol 3500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415770_2

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  • DOI: https://doi.org/10.1007/11415770_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25866-7

  • Online ISBN: 978-3-540-31950-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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