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Protein Function Prediction Based on Patterns in Biological Networks

  • Conference paper
Research in Computational Molecular Biology (RECOMB 2008)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4955))

Abstract

In this paper, we propose a pattern-based protein function annotation framework, employing protein interaction networks, to predict annotation functions of proteins. More specifically, we first detect patterns that appear in the neighborhood of proteins with a particular functionality, and then transfer annotations between two proteins only if they have similar annotation patterns. We show that, in comparison with other techniques, our approach predicts protein annotations more effectively. Our technique (a) produces the highest prediction accuracy of 70-80% precision and recall for different organism specific datasets, and (b) is robust to false positives in protein interaction networks.

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Authors and Affiliations

  1. Case Western Reserve University, Cleveland, OH, USA

    Mustafa Kirac & Gultekin Ozsoyoglu

Authors
  1. Mustafa Kirac
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  2. Gultekin Ozsoyoglu
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Martin Vingron Limsoon Wong

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Kirac, M., Ozsoyoglu, G. (2008). Protein Function Prediction Based on Patterns in Biological Networks. In: Vingron, M., Wong, L. (eds) Research in Computational Molecular Biology. RECOMB 2008. Lecture Notes in Computer Science(), vol 4955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78839-3_18

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  • DOI: https://doi.org/10.1007/978-3-540-78839-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78838-6

  • Online ISBN: 978-3-540-78839-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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