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Mathisca C M de Gunst

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BMC Bioinformatics|January 4, 2020
Bayesian mixture regression analysis for regulation of Pluripotency in ES cellsMehran Aflakparast, Geert Geeven, Mathisca C M de Gunst
Lifetime Data Analysis|July 28, 2025
Wild bootstrap for counting process-based statistics: a martingale theory-based approachMarina T Dietrich, Dennis Dobler, Mathisca C M de Gunst
Statistics in Medicine|April 30, 2003
Exploring heterogeneity in tumour data using Markov chain Monte CarloMathisca C M de Gunst, Anup Dewanji, E Georg Luebeck
Biometrical Journal. Biometrische Zeitschrift|January 11, 2018
Reconstruction of molecular network evolution from cross-sectional omics dataMehran Aflakparast, Mathisca C M de Gunst, Wessel N van Wieringen
Statistical Applications in Genetics and Molecular Biology|October 2, 2012
Comparison of targeted maximum likelihood and shrinkage estimators of parameters in gene networksGeert Geeven, Mark J van der Laan, Mathisca C M de Gunst
Neuroimage|June 15, 2015
A three domain covariance framework for EEG/MEG dataBeata P Roś, Fetsje Bijma, Mathisca C M de Gunst, et al.
Bioinformatics (Oxford, England)|November 23, 2011
Identification of context-specific gene regulatory networks with GEMULA--gene expression modeling using LAssoGeert Geeven, Ronald E van Kesteren, August B Smit, et al.
Twin Research : the Official Journal of the International Society for Twin Studies|December 21, 2004
Genetic study of the height and weight process during infancyPaula van Dommelen, Mathisca C M de Gunst, Aad W van der Vaart, et al.
FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology|March 23, 2004
Morphine exposure and abstinence define specific stages of gene expression in the rat nucleus accumbensSabine Spijker, Siard W J Houtzager, Mathisca C M De Gunst, et al.
Nucleic Acids Research|March 23, 2011
LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression dataGeert Geeven, Harold D Macgillavry, Ruben Eggers, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|January 4, 2020
Bayesian mixture regression analysis for regulation of Pluripotency in ES cellsMehran Aflakparast, Geert Geeven, Mathisca C M de Gunst
Lifetime Data Analysis|July 28, 2025
Wild bootstrap for counting process-based statistics: a martingale theory-based approachMarina T Dietrich, Dennis Dobler, Mathisca C M de Gunst
Statistics in Medicine|April 30, 2003
Exploring heterogeneity in tumour data using Markov chain Monte CarloMathisca C M de Gunst, Anup Dewanji, E Georg Luebeck
Biometrical Journal. Biometrische Zeitschrift|January 11, 2018
Reconstruction of molecular network evolution from cross-sectional omics dataMehran Aflakparast, Mathisca C M de Gunst, Wessel N van Wieringen
Statistical Applications in Genetics and Molecular Biology|October 2, 2012
Comparison of targeted maximum likelihood and shrinkage estimators of parameters in gene networksGeert Geeven, Mark J van der Laan, Mathisca C M de Gunst
Neuroimage|June 15, 2015
A three domain covariance framework for EEG/MEG dataBeata P Roś, Fetsje Bijma, Mathisca C M de Gunst, et al.
Bioinformatics (Oxford, England)|November 23, 2011
Identification of context-specific gene regulatory networks with GEMULA--gene expression modeling using LAssoGeert Geeven, Ronald E van Kesteren, August B Smit, et al.
Twin Research : the Official Journal of the International Society for Twin Studies|December 21, 2004
Genetic study of the height and weight process during infancyPaula van Dommelen, Mathisca C M de Gunst, Aad W van der Vaart, et al.
FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology|March 23, 2004
Morphine exposure and abstinence define specific stages of gene expression in the rat nucleus accumbensSabine Spijker, Siard W J Houtzager, Mathisca C M De Gunst, et al.
Nucleic Acids Research|March 23, 2011
LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression dataGeert Geeven, Harold D Macgillavry, Ruben Eggers, et al.
Pageof 2