Qualitative modeling of normal blood coagulation and its pathological states using stochastic activity networks.
We have developed a method for representing biological pathways and simulating their behavior based on the use of stochastic activity networks (SANs). SANs, an extension of the original Petri net, have been used traditionally to model flow systems including data-communications networks and manufacturing processes. We apply the methodology to the blood coagulation cascade, a biological flow system, and present the representation method as well as results of simulation studies based on published experimental data. In addition to describing the dynamic model, we also present the results of its utilization to perform simulations of clinical states including hemophilia's A and B as well as sensitivity analysis of individual factors and their impact on thrombin production.
Mounts
W M
WM
Vysis, Inc., Downers Grove, IL 60515, USA.
Liebman
M N
MN
D001777:Blood Coagulation / Q000502:physiology*; D003198:Computer Simulation; D005164:Factor IX / Q000378:metabolism; D005165:Factor V / Q000378:metabolism; D005169:Factor VIII / Q000378:metabolism; D005170:Factor X / Q000378:metabolism; D006467:Hemophilia A / Q000378:metabolism / Q000503:physiopathology*; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D016571:Neural Networks, Computer; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D014357:Trypsin / Q000378:metabolism; D014362:Trypsinogen / Q000378:metabolism
D005165:Factor V; D005169:Factor VIII; D005164:Factor IX; D005170:Factor X; D014362:Trypsinogen; D014357:Trypsin