Abstract:
This paper is concerned with the problem of identifying a discrete-time dynamical system model for a gene regulatory network with unknown topology using time series gene ...Show MoreMetadata
Abstract:
This paper is concerned with the problem of identifying a discrete-time dynamical system model for a gene regulatory network with unknown topology using time series gene expression data. The topology of such a network can be characterized by a set of regulation hypotheses, one for each gene. In our earlier work, we formulated a convex optimization method to select the regulation hypotheses (and hence the network topology). In this paper, we further optimize the dynamics of the inferred network. Specifically, for a given topology, we minimize the ℓ2 distance between the experimental data and the model prediction. We illustrate the performance of our algorithm by identifying models for gene networks with known topology.
Published in: 52nd IEEE Conference on Decision and Control
Date of Conference: 10-13 December 2013
Date Added to IEEE Xplore: 10 March 2014
ISBN Information:
Print ISSN: 0191-2216