TY - JOUR AU - Creamer, Matthew S. AU - Stites, Edward C. AU - Aziz, Meraj AU - Cahill, James A. AU - Tan, Chin Wee AU - Berens, Michael E. AU - Han, Haiyong AU - Bussey, Kimberley J. AU - Von Hoff, Daniel D. AU - Hlavacek, William S. AU - Posner, Richard G. PY - 2012 DA - 2012/08/22 TI - Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling JO - BMC Systems Biology SP - 107 VL - 6 IS - 1 AB - Mathematical/computational models are needed to understand cell signaling networks, which are complex. Signaling proteins contain multiple functional components and multiple sites of post-translational modification. The multiplicity of components and sites of modification ensures that interactions among signaling proteins have the potential to generate myriad protein complexes and post-translational modification states. As a result, the number of chemical species that can be populated in a cell signaling network, and hence the number of equations in an ordinary differential equation model required to capture the dynamics of these species, is prohibitively large. To overcome this problem, the rule-based modeling approach has been developed for representing interactions within signaling networks efficiently and compactly through coarse-graining of the chemical kinetics of molecular interactions. SN - 1752-0509 UR - https://doi.org/10.1186/1752-0509-6-107 DO - 10.1186/1752-0509-6-107 ID - Creamer2012 ER -