High-Dimensional ODEs Coupled With Mixed-Effects Modeling Techniques for Dynamic Gene Regulatory Network Identification

From MaRDI portal
Publication:3225789

DOI10.1198/jasa.2011.ap10194zbMath1234.62146OpenAlexW2025825535WikidataQ41813504 ScholiaQ41813504MaRDI QIDQ3225789

Hulin Wu, Hongzhe Li, Hua Liang, Tao Lü

Publication date: 22 March 2012

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3509540




Related Items (17)

Dynamical modeling for non-Gaussian data with high-dimensional sparse ordinary differential equationsIdentifiability analysis of linear ordinary differential equation systems with a single trajectoryAPIK: Active Physics-Informed Kriging Model with Partial Differential EquationsA joint estimation approach to sparse additive ordinary differential equationsEstimating Varying Coefficients for Partial Differential Equation ModelsKernel Ordinary Differential EquationsTopological sensitivity analysis for systems biologyBayesian detection of event spreading pattern from multivariate binary time seriesJoint Structural Break Detection and Parameter Estimation in High-Dimensional Nonstationary VAR ModelsStatistical inference in mechanistic models: time warping for improved gradient matchingAsymptotically efficient parameter estimation for ordinary differential equationsBayesian analysis of mixed-effect regression models driven by ordinary differential equationsBayesian inference of a directional brain network model for intracranial EEG dataTiming observations of diffusionsInvestigate Data Dependency for Dynamic Gene Regulatory Network Identification through High-dimensional Differential Equation ApproachSparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network ModelingParameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach


Uses Software



This page was built for publication: High-Dimensional ODEs Coupled With Mixed-Effects Modeling Techniques for Dynamic Gene Regulatory Network Identification