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Statistical Model Checking in BioLab: Applications to the Automated Analysis of T-Cell Receptor Signaling Pathway

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Computational Methods in Systems Biology (CMSB 2008)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5307))

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Abstract

We present an algorithm, called BioLab, for verifying temporal properties of rule-based models of cellular signalling networks.

BioLab models are encoded in the BioNetGen language, and properties are expressed as formulae in probabilistic bounded linear temporal logic. Temporal logic is a formalism for representing and reasoning about propositions qualified in terms of time. Properties are then verified using sequential hypothesis testing on executions generated using stochastic simulation. BioLab is optimal, in the sense that it generates the minimum number of executions necessary to verify the given property. BioLab also provides guarantees on the probability of it generating Type-I (i.e., false-positive) and Type-II (i.e., false-negative) errors. Moreover, these error bounds are pre-specified by the user. We demonstrate BioLab by verifying stochastic effects and bistability in the dynamics of the T-cell receptor signaling network.

This research was sponsored by the GSRC (University of California) under contract no. SA423679952, National Science Foundation under contracts no. CCF0429120, no. CNS0411152, and no. CCF0541245, Semiconductor Research Corporation under contract no. 2005TJ1366, Air Force (University of Vanderbilt) under contract no. 18727S3, International Collaboration for Advanced Security Technology of the National Science Council, Taiwan, under contract no. 1010717, the Belgian American Educational Foundation, the U.S. Department of Energy Career Award (DE-FG02-05ER25696), a Pittsburgh Life-Sciences Greenhouse Young Pioneer Award, National Institutes of Health grant GM76570 and a B.A.E.F grant.

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Authors and Affiliations

  1. Computer Science Department, Carnegie Mellon University, Pittsburgh, PA

    Edmund M. Clarke, Christopher J. Langmead, Sumit Kumar Jha & Axel Legay

  2. Department of Computational Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA

    James R. Faeder & Leonard A. Harris

Authors
  1. Edmund M. Clarke
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  2. James R. Faeder
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  3. Christopher J. Langmead
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  4. Leonard A. Harris
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  5. Sumit Kumar Jha
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  6. Axel Legay
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Editors and Affiliations

  1. Department of Computer Science, Brandenburg University of Technology, Postbox 10 13 44, 03013, Cottbus, Germany

    Monika Heiner

  2. University of Rostock, Albert-Einstein-Str. 21, D-18059, Rostock, Germany

    Adelinde M. Uhrmacher

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Clarke, E.M., Faeder, J.R., Langmead, C.J., Harris, L.A., Jha, S.K., Legay, A. (2008). Statistical Model Checking in BioLab: Applications to the Automated Analysis of T-Cell Receptor Signaling Pathway. In: Heiner, M., Uhrmacher, A.M. (eds) Computational Methods in Systems Biology. CMSB 2008. Lecture Notes in Computer Science(), vol 5307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88562-7_18

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  • DOI: https://doi.org/10.1007/978-3-540-88562-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88561-0

  • Online ISBN: 978-3-540-88562-7

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