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Representing Dynami...
Representing Dynamic Biological Networks With Multi-Scale Probabilistic Models
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- Groß, Alexander (author)
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
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- Kracher, Barbara (author)
- Institute of Biochemistry and Molecular Biology, Ulm University, Ulm, Germany
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- Kraus, Johann M. (author)
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
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- Kühlwein, Silke D. (author)
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
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- Pfister, Astrid S. (author)
- Institute of Biochemistry and Molecular Biology, Ulm University, Ulm, Germany
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- Wiese, Sebastian (author)
- Core Unit Mass Spectrometry and Proteomics, Ulm University, Ulm, Germany
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- Luckert, Katrin (author)
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
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- Pötz, Oliver (author)
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
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- Joos, Thomas (author)
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
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- Van Daele, Dries (author)
- Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium
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- De Raedt, Luc, 1964- (author)
- Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium
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- Kühl, Michael (author)
- Institute of Biochemistry and Molecular Biology, Ulm University, Ulm, Germany
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- Kestler, Hans A. (author)
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
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(creator_code:org_t)
- 2019-01-17
- 2019
- English.
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In: Communications Biology. - : Springer Nature. - 2399-3642. ; 2
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https://doi.org/10.1...
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Abstract
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- Dynamic models analyzing gene regulation and metabolism face challenges when adapted to modeling signal transduction networks. During signal transduction, molecular reactions and mechanisms occur in different spatial and temporal frames and involve feedbacks. This impedes the straight-forward use of methods based on Boolean networks, Bayesian approaches, and differential equations. We propose a new approach, ProbRules, that combines probabilities and logical rules to represent the dynamics of a system across multiple scales. We demonstrate that ProbRules models can represent various network motifs of biological systems. As an example of a comprehensive model of signal transduction, we provide a Wnt network that shows remarkable robustness under a range of phenotypical and pathological conditions. Its simulation allows the clarification of controversially discussed molecular mechanisms of Wnt signaling by predicting wet-lab measurements. ProbRules provides an avenue in current computational modeling by enabling systems biologists to integrate vast amounts of available data on different scales.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Groß, Alexander
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Kracher, Barbara
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Kraus, Johann M.
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Kühlwein, Silke ...
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Pfister, Astrid ...
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Wiese, Sebastian
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show more...
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Luckert, Katrin
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Pötz, Oliver
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Joos, Thomas
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Van Daele, Dries
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De Raedt, Luc, 1 ...
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Kühl, Michael
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Kestler, Hans A.
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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Bioinformatics
- Articles in the publication
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Communications B ...
- By the university
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Örebro University