Journal
JOURNAL OF COMPUTATIONAL BIOLOGY
Volume 16, Issue 5, Pages 725-743Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2008.0163
Keywords
biological signaling networks; integer programming; modeling; monotone boolean functions; satisfiability
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Funding
- German Ministry of Education
- Magdeburg Center for Systems Biology (MaCS)
- Kultusministerium of Saxony-Anhalt
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We 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.
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