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 | 1922 | 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 | 430 | 2006 |
Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move M Grzegorczyk, D Husmeier Machine Learning 71 (2), 265-305, 2008 | 197 | 2008 |
Non-stationary continuous dynamic Bayesian networks M Grzegorczyk, D Husmeier Advances in neural information processing systems 22, 2009 | 119 | 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 | 100 | 2011 |
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 | 100 | 2008 |
Non-homogeneous dynamic Bayesian networks for continuous data M Grzegorczyk, D Husmeier Machine Learning 83, 355-419, 2011 | 95 | 2011 |
Statistics for proteomics: a review of tools for analyzing experimental data W Urfer, M Grzegorczyk, K Jung Proteomics 6 (S2), 48-55, 2006 | 75 | 2006 |
An introduction to Gaussian Bayesian networks M Grzegorczyk Systems biology in drug discovery and development: methods and protocols …, 2010 | 54 | 2010 |
Nonparametric bayesian networks K Ickstadt, B Bornkamp, M Grzegorczyk, J Wieczorek, MR Sheriff, ... Bayesian statistics 9, 283-316, 2010 | 48 | 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 | 37 | 2014 |
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 | 34 | 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), 2012 | 34 | 2012 |
Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models M Grzegorczyk, D Husmeier Machine Learning 91, 105-154, 2013 | 32 | 2013 |
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 | 31 | 2005 |
Reverse engineering gene regulatory networks with various machine learning methods M Grzegorczyk, D Husmeier, A Werhli Wiley-VCH, 2008 | 29 | 2008 |
Bayesian network based procedure for regional drought monitoring: the seasonally combinative regional drought indicator Z Ali, I Hussain, MA Grzegorczyk, G Ni, M Faisal, S Qamar, AM Shoukry, ... Journal of Environmental Management 276, 111296, 2020 | 28 | 2020 |
A probabilistic weighted joint aggregative drought index (PWJADI) criterion for drought monitoring systems Z Ali, I Hussain, M Faisal, IM Almanjahie, I Ahmad, DM Khan, ... Tellus A: Dynamic Meteorology and Oceanography 71 (1), 1588584, 2019 | 27 | 2019 |
Approximate Bayesian inference in semi-mechanistic models A Aderhold, D Husmeier, M Grzegorczyk Statistics and Computing 27, 1003-1040, 2017 | 23 | 2017 |
Gene network approach reveals co-expression patterns in nasal and bronchial epithelium K Imkamp, V Bernal, M Grzegorzcyk, P Horvatovich, CJ Vermeulen, ... Scientific Reports 9 (1), 15835, 2019 | 20 | 2019 |