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Context-Specific Nested Effects Models

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Research in Computational Molecular Biology (RECOMB 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10812))

Abstract

Advances in systems biology have made clear the importance of network models for capturing knowledge about complex relationships in gene regulation, metabolism, and cellular signaling. A common approach to uncovering biological networks involves performing perturbations on elements of the network, such as gene knockdown experiments, and measuring how the perturbation affects some reporter of the process under study. In this paper, we develop context-specific nested effects models (CSNEMs), an approach to inferring such networks that generalizes nested effect models (NEMs). The main contribution of this work is that CSNEMs explicitly model the participation of a gene in multiple contexts, meaning that a gene can appear in multiple places in the network. Biologically, the representation of regulators in multiple contexts may indicate that these regulators have distinct roles in different cellular compartments or cell cycle phases. We present an evaluation of the method on simulated data as well as on data from a study of the sodium chloride stress response in Saccharomyces cerevisiae.

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Notes

  1. 1.

    For a detailed derivation see https://github.com/sverchkov/mc-em-cs-nem/blob/master/recomb-2018-supplement/recomb-2018-supplement.pdf, commit 98b01f19357e3d58eae81764d42a6903624e3433 at the time of submission.

  2. 2.

    An NEM learned from the data is at https://github.com/sverchkov/mc-em-cs-nem/blob/master/recomb-2018-supplement/recomb-2018-supplement.pdf.

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Acknowledgments

We thank anonymous reviewers for many constructive comments. This research was supported by NIH/NLM grant T15 LM0007359, NIH/NIAID grant U54 AI117954, and NIH/NIGMS grant R01 GM083989.

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Authors and Affiliations

  1. Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Madison, WI, USA

    Yuriy Sverchkov & Mark Craven

  2. Department of Genetics, University of Wisconsin–Madison, Madison, WI, USA

    Yi-Hsuan Ho & Audrey Gasch

Authors
  1. Yuriy Sverchkov
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  2. Yi-Hsuan Ho
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  3. Audrey Gasch
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  4. Mark Craven
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Corresponding author

Correspondence to Yuriy Sverchkov .

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Editors and Affiliations

  1. Computer Science Department, Princeton University, Princeton, New Jersey, USA

    Benjamin J. Raphael

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Sverchkov, Y., Ho, YH., Gasch, A., Craven, M. (2018). Context-Specific Nested Effects Models. In: Raphael, B. (eds) Research in Computational Molecular Biology. RECOMB 2018. Lecture Notes in Computer Science(), vol 10812. Springer, Cham. https://doi.org/10.1007/978-3-319-89929-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-89929-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-89928-2

  • Online ISBN: 978-3-319-89929-9

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