Logic-based models for the analysis of cell signaling networks.
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.
Center for Cell Decision Process and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Melody K
MK
Morris
Julio
J
Saez-Rodriguez
Peter K
PK
Sorger
Douglas A
DA
Lauffenburger
D001671:Biochemistry / Q000379:methods / Q000639:trends; D002468:Cell Physiological Phenomena; D039301:Computers, Molecular; D017143:Fuzzy Logic; D007700:Kinetics; D008128:Logic; D008954:Models, Biological; D008967:Molecular Biology / Q000379:methods / Q000639:trends; D011506:Proteins / Q000502:physiology; D015398:Signal Transduction / Q000502:physiology*
D011506:Proteins