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Automatic Parameter Learning for Multiple Network Alignment

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Research in Computational Molecular Biology (RECOMB 2008)

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

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Abstract

We developed Græmlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (2) a parameter learning algorithm that uses a training set of known network alignments to learn parameters for our scoring function and thereby adapt it to any set of networks; and (3) an algorithm that uses our scoring function to find approximate multiple network alignments in linear time.

We tested Græmlin 2.0’s accuracy on protein interaction networks from IntAct, DIP, and the Stanford Network Database. We show that, on each of these datasets, Græmlin 2.0 has higher sensitivity and specificity than existing network aligners. Græmlin 2.0 is available under the GNU public license at http://graemlin.stanford.edu.

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Authors and Affiliations

  1. Department of Computer Science, Stanford University, Stanford, CA 94305, USA

    Jason Flannick, Antal Novak, Chuong B. Do & Serafim Batzoglou

  2. Department of Statistics, Stanford University, Stanford, CA 94305, USA

    Balaji S. Srinivasan

Authors
  1. Jason Flannick
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  2. Antal Novak
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  3. Chuong B. Do
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  4. Balaji S. Srinivasan
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  5. Serafim Batzoglou
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Martin Vingron Limsoon Wong

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© 2008 Springer-Verlag Berlin Heidelberg

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Flannick, J., Novak, A., Do, C.B., Srinivasan, B.S., Batzoglou, S. (2008). Automatic Parameter Learning for Multiple Network Alignment. 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_19

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  • DOI: https://doi.org/10.1007/978-3-540-78839-3_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78838-6

  • Online ISBN: 978-3-540-78839-3

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