Following is a description of a recently published research paper recommended by a scientist involved in integrated biology. The recommender, Anuj Kumar, is an assistant professor in molecular, cellular, and developmental biology at the
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"In silico simulation of biological network dynamics," Lukasz Salwinski and David Eisenberg. Nature Biotechnology. 2004; 22 (9): 1017-1019.
"In this paper, the authors describe an approach to simulating biological networks using field programmable gate arrays, whose parallel architecture allows for more realistic simulation of the reaction steps in biological networks, according to the paper's abstract. They say that in the past such large-scale simulations have been limited both by data availability and by the vast computational demands for the stochastic algorithms needed to model the networks.
"'With the rise of various -omics approaches, the limitation of experimental data is being lifted, but the computational demands remain staggering for simulating networks of thousands of reactions involving thousands of reactants,' the authors note. 'The problem stems from the sequential nature of microprocessor architecture and the highly parallel nature of biological systems, with the result that simulation times become prohibitively long.' The authors say using FPGAs can improve simulation run times by 'at least an order of magnitude' over what conventional microprocessors can achieve."