A data-driven computational model of the ErbB receptor signaling network.
Signal transduction networks are often described by qualitative models that incorporate experimental findings from different cell types. However, a large body of evidence suggests that cell signaling differs substantially from one cell type to the next. Even in cases in which the topology of signaling networks is conserved, different cell types respond differently under the same experimental conditions. In this work we address the problem of developing quantitative and cell-type specific models of cells signaling that incorporate experimental data obtained from protein arrays and mathematical modeling. As a biological system we examine signaling mediated ErbB receptor family as the current literature is very controversial.
Schoeberl
Birgit
B
Merrimack Pharmaceuticals, Cambridge, MA 02141, USA.
Pace
Emily
E
Howard
Shavonne
S
Garantcharova
Viara
V
Kudla
Art
A
Sorger
Peter K
PK
Nielsen
Ulrik B
UB
D003198:Computer Simulation; D016208:Databases, Factual; D004815:Epidermal Growth Factor / Q000378:metabolism*; D066246:ErbB Receptors / Q000378:metabolism*; D008954:Models, Biological; D011505:Protein-Tyrosine Kinases / Q000378:metabolism*; D015398:Signal Transduction / Q000187:drug effects / Q000502:physiology*
D004815:Epidermal Growth Factor; D066246:ErbB Receptors; D011505:Protein-Tyrosine Kinases