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Computation of biochemical pathway fluctuations beyond the linear noise approximation using iNA

机译:使用iNA计算超出线性噪声近似值的生化途径波动

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The linear noise approximation is commonly used to obtain intrinsic noise statistics for biochemical networks. These estimates are accurate for networks with large numbers of molecules. However it is well known that many biochemical networks are characterized by at least one species with a small number of molecules. We here describe version 0.3 of the software intrinsic Noise Analyzer (iNA) which allows for accurate computation of noise statistics over wide ranges of molecule numbers. This is achieved by calculating the next order corrections to the linear noise approximation's estimates of variance and covariance of concentration fluctuations. The efficiency of the methods is significantly improved by automated just-in-time compilation using the LLVM framework leading to a fluctuation analysis which typically outperforms that obtained by means of exact stochastic simulations. iNA is hence particularly well suited for the needs of the computational biology community.
机译:线性噪声近似通常用于获取生化网络的固有噪声统计数据。这些估计对于具有大量分子的网络是准确的。然而,众所周知,许多生化网络的特征在于至少一种具有少量分子的物种。我们在此介绍软件固有噪声分析器(iNA)的0.3版,该软件可在广泛的分子数范围内准确计算噪声统计信息。这是通过对浓度波动的方差和协方差的线性噪声近似估计值进行下一阶校正来实现的。通过使用LLVM框架进行实时自动编译,可显着提高方法的效率,从而导致波动分析,其性能通常优于通过精确随机模拟获得的波动分析。因此,iNA特别适合计算生物学界的需求。

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