| Wisdom of crowds for robust gene network inference D Marbach, JC Costello, R Küffner, NM Vega, RJ Prill, DM Camacho, ... Nature methods 9 (8), 796-804, 2012 | 1334 | 2012 |
| Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical Gaussian models and Bayesian networks AV Werhli, M Grzegorczyk, D Husmeier Bioinformatics 22 (20), 2523-2531, 2006 | 390 | 2006 |
| Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move M Grzegorczyk, D Husmeier Machine Learning 71 (2-3), 265, 2008 | 138 | 2008 |
| Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler M Grzegorczyk, D Husmeier, KD Edwards, P Ghazal, AJ Millar Bioinformatics 24 (18), 2071-2078, 2008 | 93 | 2008 |
| Non-stationary continuous dynamic Bayesian networks M Grzegorczyk, D Husmeier Curran Associates, 2009 | 90 | 2009 |
| Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes M Grzegorczyk, D Husmeier Bioinformatics 27 (5), 693-699, 2011 | 81 | 2011 |
| Non-homogeneous dynamic Bayesian networks for continuous data M Grzegorczyk, D Husmeier Machine Learning 83 (3), 355-419, 2011 | 75 | 2011 |
| Statistics for proteomics: a review of tools for analyzing experimental data W Urfer, M Grzegorczyk, K Jung Proteomics 6 (S2), 48-55, 2006 | 66 | 2006 |
| Nonparametric bayesian networks K Ickstadt, B Bornkamp, M Grzegorczyk, J Wieczorek, MR Sheriff, ... Bayesian Stat 9, 283, 2011 | 34 | 2011 |
| An introduction to Gaussian Bayesian networks M Grzegorczyk Systems Biology in Drug Discovery and Development, 121-147, 2010 | 32 | 2010 |
| Statistical inference of regulatory networks for circadian regulation A Aderhold, D Husmeier, M Grzegorczyk Statistical applications in genetics and molecular biology 13 (3), 227-273, 2014 | 31 | 2014 |
| Non-invasive detection of colorectal tumours by the combined application of molecular diagnosis and the faecal occult blood test N Kutzner, I Hoffmann, C Linke, T Thienel, M Grzegorczyk, W Urfer, ... Cancer letters 229 (1), 33-41, 2005 | 30 | 2005 |
| Reverse engineering gene regulatory networks with various machine learning methods M Grzegorczyk, D Husmeier, A Werhli Analysis of Microarray Data. Weinheim: Wiley-VCH, 101-142, 2008 | 27 | 2008 |
| A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points M Grzegorczyk Machine learning 102 (2), 155-207, 2016 | 23 | 2016 |
| A non-homogeneous dynamic Bayesian network with sequentially coupled interaction parameters for applications in systems and synthetic biology M Grzegorczyk, D Husmeier Statistical applications in genetics and molecular biology 11 (4), Art. 7, 2012 | 23 | 2012 |
| Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models M Grzegorczyk, D Husmeier Machine Learning 91 (1), 105-154, 2013 | 20 | 2013 |
| Approximate Bayesian inference in semi-mechanistic models A Aderhold, D Husmeier, M Grzegorczyk Statistics and Computing 27 (4), 1003-1040, 2017 | 16 | 2017 |
| Absolute β-catenin concentrations in Wnt pathway-stimulated and non-stimulated cells S Sievers, C Fritzsch, M Grzegorczyk, C Kuhnen, O Müller Biomarkers 11 (3), 270-278, 2006 | 16 | 2006 |
| Modelling non-stationary dynamic gene regulatory processes with the BGM model M Grzegorczyk, D Husmeier, J Rahnenführer Computational Statistics 26 (2), 199-218, 2011 | 15 | 2011 |
| Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters M Grzegorzyk, D Husmeier Artificial Intelligence and Statistics, 467-476, 2012 | 11 | 2012 |
