Showing results (21-30 of 84) with videos related to
Sort By:
Pageof 9
Methods in Molecular Biology (Clifton, N.J.)|December 15, 2018
Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series DataMarco Grzegorczyk, Andrej Aderhold, Dirk HusmeierStatistical Applications in Genetics and Molecular Biology|May 28, 2014
Statistical inference of regulatory networks for circadian regulationAndrej Aderhold, Dirk Husmeier, Marco GrzegorczykBioinformatics (Oxford, England)|December 2, 2004
Detecting interspecific recombination with a pruned probabilistic divergence measureDirk Husmeier, Frank Wright, Iain MilneMethods in Molecular Biology (Clifton, N.J.)|December 2, 2011
Nonhomogeneous dynamic Bayesian networks in systems biologySophie Lèbre, Frank Dondelinger, Dirk HusmeierAdvances in Bioinformatics|August 20, 2010
Modelling nonstationary gene regulatory processesMarco Grzegorcyzk, Dirk Husmeier, Jörg RahnenführerBioinformatics (Oxford, England)|July 18, 2006
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networksAdriano V Werhli, Marco Grzegorczyk, Dirk HusmeierInternational Journal for Numerical Methods in Biomedical Engineering|March 18, 2022
Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricleAgnieszka Borowska, Hao Gao, Alan Lazarus, et al.Movement Ecology|February 19, 2021
A hierarchical machine learning framework for the analysis of large scale animal movement dataColin J Torney, Juan M Morales, Dirk HusmeierBiomechanics and Modeling in Mechanobiology|April 4, 2022
Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanicsAlan Lazarus, David Dalton, Dirk Husmeier, et al.Computational Statistics|July 15, 2025
Approximate Bayesian inference in a model for self-generated gradient collective cell movementJon Devlin, Agnieszka Borowska, Dirk Husmeier, et al.Pageof 9