Original paper

Network Reconstruction From High-Dimensional Ordinary Differential Equations

Volume: 112, Issue: 520, Pages: 1697 - 1707
Published: Aug 7, 2017
Abstract
We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy...
Paper Details
Title
Network Reconstruction From High-Dimensional Ordinary Differential Equations
Published Date
Aug 7, 2017
Volume
112
Issue
520
Pages
1697 - 1707
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.