S-system parameter estimation for noisy metabolic profiles using Newton-flow analysis

• Biochemical systems are commonly modelled by systems of ordinary differentialequations (ODEs). A particular class of such models called S-systems have recently gained popu-larity in biochemical system modelling. The parameters of an S-system are usually estimated fromtime-course profiles. However, finding these estimates is a difficult computational problem.Moreover, although several methods have been recently proposed to solve this problem for idealprofiles, relatively little progress has been reported for noisy profiles. We describe a specialfeature of a Newton-flow optimisation problem associated with S-system parameter estimation.This enables us to significantly reduce the search space, and also lends itself to parameter esti-mation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems.In addition, we propose an extension of our method that allows the detection of network topologiesfor small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competingmethods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Ämnesord

NATURVETENSKAP  -- Biologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

Nyckelord

Biology

Biologi

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