Logic Integer Programming Models for Signaling Networks

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dc.creatorHaus, Utz-Uwe
dc.creatorNiermann, Kathrin
dc.creatorTruemper, Klaus
dc.creatorWeismantel, Robert
dc.date2008-08-28
dc.date.accessioned2026-07-07T13:13:51Z
dc.date.available2026-07-07T13:13:51Z
dc.descriptionWe propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in Molecular Biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.
dc.identifierhttps://arxiv.org/abs/0808.3870
dc.identifierhttp://arxiv.org/abs/0808.3870
dc.identifierJournal of Computational Biology. May 2009, 16(5): 725-743
dc.identifierdoi:10.1089/cmb.2008.0163
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/230027
dc.subjectQuantitative Methods
dc.subjectCell Behavior
dc.titleLogic Integer Programming Models for Signaling Networks
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