Manatee invariants reveal functional pathways in signaling networks View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Leonie Amstein, Jörg Ackermann, Jennifer Scheidel, Simone Fulda, Ivan Dikic, Ina Koch

ABSTRACT

BACKGROUND: Signal transduction pathways are important cellular processes to maintain the cell's integrity. Their imbalance can cause severe pathologies. As signal transduction pathways feature complex regulations, they form intertwined networks. Mathematical models aim to capture their regulatory logic and allow an unbiased analysis of robustness and vulnerability of the signaling network. Pathway detection is yet a challenge for the analysis of signaling networks in the field of systems biology. A rigorous mathematical formalism is lacking to identify all possible signal flows in a network model. RESULTS: In this paper, we introduce the concept of Manatee invariants for the analysis of signal transduction networks. We present an algorithm for the characterization of the combinatorial diversity of signal flows, e.g., from signal reception to cellular response. We demonstrate the concept for a small model of the TNFR1-mediated NF- κB signaling pathway. Manatee invariants reveal all possible signal flows in the network. Further, we show the application of Manatee invariants for in silico knockout experiments. Here, we illustrate the biological relevance of the concept. CONCLUSIONS: The proposed mathematical framework reveals the entire variety of signal flows in models of signaling systems, including cyclic regulations. Thereby, Manatee invariants allow for the analysis of robustness and vulnerability of signaling networks. The application to further analyses such as for in silico knockout was shown. The new framework of Manatee invariants contributes to an advanced examination of signaling systems. More... »

PAGES

72

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12918-017-0448-7

    DOI

    http://dx.doi.org/10.1186/s12918-017-0448-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1090915717

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28754124


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    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12918-017-0448-7'

    Turtle is a human-readable linked data format.

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    RDF/XML is a standard XML format for linked data.

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