title: Discrete, qualitative models of interaction networks.
abstract: Logical models for cellular signaling networks are recently attracting wide interest: Their ability to integrate qualitative information at different biological levels, from receptor-ligand interactions to gene-regulatory networks, is becoming essential for understanding complex signaling behavior. We present an overview of Boolean modeling paradigms and discuss in detail an approach based on causal logical interactions that yields descriptive and predictive signaling network models. Our approach offers a mathematically well-defined concept, improving the efficiency of analytical tools to meet the demand of large-scale data sets, and can be extended into various directions to include timing information as well as multiple discrete values for components.
authors.affiliation: Institute of Operations Research, Department of Mathematics, ETH Zurich, Zurich, Switzerland.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Ballerstein
authors.forename: Utz-Uwe
authors.initials: UU
authors.lastname: Haus
authors.forename: Jonathan Axel
authors.initials: JA
authors.lastname: Lindquist
authors.forename: Tilo
authors.initials: T
authors.lastname: Beyer
authors.forename: Burkhart
authors.initials: B
authors.lastname: Schraven
authors.forename: Robert
authors.initials: R
authors.lastname: Weismantel
mesh_terms: D053263:Gene Regulatory Networks; D008024:Ligands; D008954:Models, Biological; D011956:Receptors, Cell Surface / Q000378:metabolism; D015398:Signal Transduction
chemical_list: D008024:Ligands; D011956:Receptors, Cell Surface