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Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

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Research in Computational Molecular Biology (RECOMB 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6577))

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Abstract

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Tufts University, 161 College Ave, Medford, MA, 02155, USA

    Mark D. M. Leiserson, Diana Tatar, Lenore J. Cowen & Benjamin J. Hescott

Authors
  1. Mark D. M. Leiserson
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  2. Diana Tatar
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  3. Lenore J. Cowen
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  4. Benjamin J. Hescott
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Editor information

Editors and Affiliations

  1. EBU3b, University of California San Diego, #4218, 9500 Gilman Drive, 92093-0404, La Jolla, CA, USA

    Vineet Bafna

  2. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    S. Cenk Sahinalp

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© 2011 Springer-Verlag Berlin Heidelberg

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Leiserson, M.D.M., Tatar, D., Cowen, L.J., Hescott, B.J. (2011). Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut. In: Bafna, V., Sahinalp, S.C. (eds) Research in Computational Molecular Biology. RECOMB 2011. Lecture Notes in Computer Science(), vol 6577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20036-6_17

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  • DOI: https://doi.org/10.1007/978-3-642-20036-6_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20035-9

  • Online ISBN: 978-3-642-20036-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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