The implementation of efficient methods to infer mathematical models of biochemical phenomena from experimental data is necessary to understand the dynamics of such types of systems and their regulative mechanisms, and it is also a central issue in Systems Biology. This work presents an initial investigation on the use of the Nvidia Tesla C1060 GPUs, in the context of a Reverse Engineering Dynamics pipeline that we intend to develop and apply to regulatory parameters estimation and simulation of biological networks. As an example, we focus on flux estimation of a nuclear receptor signalling pathway involved in metabolic diseases like diabetes and dyslipidemia and on a synthetic model for performance comparison.
Towards a GPU-aided simulation of nuclear receptors modulation
PAGLIARINI, Roberto;
2009-01-01
Abstract
The implementation of efficient methods to infer mathematical models of biochemical phenomena from experimental data is necessary to understand the dynamics of such types of systems and their regulative mechanisms, and it is also a central issue in Systems Biology. This work presents an initial investigation on the use of the Nvidia Tesla C1060 GPUs, in the context of a Reverse Engineering Dynamics pipeline that we intend to develop and apply to regulatory parameters estimation and simulation of biological networks. As an example, we focus on flux estimation of a nuclear receptor signalling pathway involved in metabolic diseases like diabetes and dyslipidemia and on a synthetic model for performance comparison.
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