Robust model invalidation for chemical reaction networks using generalized moments (extended version)
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root.pdf
Description
Main article
Size
1.17 MB
Format
Adobe PDF
Checksum (MD5)
90edb4738b3d4ca89443b4ce825b45df
Author(s)
Grunberg, Theodore W.
Del Vecchio, Domitilla
Date Issued
March 31, 2023
Abstract
Many biomolecular systems can be described by chemical reaction networks. Determining which chemical reaction network models are inconsistent with observed data can be done via model invalidation. In this work, we formulate and solve a robust version of the model invalidation problem for the case where only measurements from the stationary distribution are available. This problem corresponds to determining if an observed distribution could have been generated by the given chemical reaction network for some value of the parameters, plus a perturbation of bounded size with respect to total variation distance. The main technical tool we introduce to solve the problem is a set of generalized moments that make the problem amenable to an algorithmic solution.
Description
Extended version
Subjects
synthetic biology
model invalidation
system identification
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