In silico simulation of biological network dynamics.
Realistic simulation of biological networks requires stochastic simulation approaches because of the small numbers of molecules per cell. The high computational cost of stochastic simulation on conventional microprocessor-based computers arises from the intrinsic disparity between the sequential steps executed by a microprocessor program and the highly parallel nature of information flow within biochemical networks. This disparity is reduced with the Field Programmable Gate Array (FPGA)-based approach presented here. The parallel architecture of FPGAs, which can simulate the basic reaction steps of biological networks, attains simulation rates at least an order of magnitude greater than currently available microprocessors.
Salwinski
Lukasz
L
UCLA-DOE Institute for Genomics and Proteomics, Howard Hughes Medical Institute, Molecular Biology Institute, Los Angeles, CA 90095-1570, USA.
Eisenberg
David
D
D000465:Algorithms; D000818:Animals; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D003205:Computing Methodologies; D005240:Feasibility Studies; D005786:Gene Expression Regulation / Q000502:physiology; D006801:Humans; D007700:Kinetics; D008660:Metabolism / Q000502:physiology; D008954:Models, Biological; D015233:Models, Statistical; D009097:Multienzyme Complexes / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D013269:Stochastic Processes
D009097:Multienzyme Complexes