Logic-Based Models for the Analysis of Cell Signaling Networks

By Melody K. Morris, J. Sáez-Rodríguez, Peter K. Sorger, Douglas A. Lauffenburger. Biochemistry, 2010

354 citations recorded by the source corpus.

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ebaee5794622a78090ebe5d1a03758b85a82fbd3

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In Molecular Biology

Citations in the corpus

Pathway and Network Analysis of Cancer Genomes (2015, positive): “Functions of discrete logic were used to connect gene products through “gates” 61 and to infer functions best capturing the observed dynamics in the data.”
Systems biology approaches for advancing the discovery of effective drug combinations (2015, background): “Each species in the network takes a value of 0 (inactive) or 1 (active) based on the state of its effectors [29].”
A Directed Protein Interaction Network for Investigating Intracellular Signal Transduction (2011, background): “Although the interactions lack sign ( 12 ), the directed PPI network supports various modeling strategies and improves the power of predictions made from PPI network analyses ( 13 , 14 , 52 ).”