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

TL;DR

This paper introduces iNA version 0.3, a software tool that accurately computes biochemical pathway fluctuations beyond the linear noise approximation, especially for species with low molecule counts, using advanced correction methods.

Contribution

The paper presents an improved version of iNA that calculates next-order corrections to noise estimates, outperforming stochastic simulations in efficiency.

Findings

iNA 0.3 provides accurate noise statistics for small molecule numbers.

The software outperforms exact stochastic simulations in speed.

Automated just-in-time compilation enhances computational efficiency.

Abstract

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.