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Dr. Marco Andreas Grzegorczyk

  • room number:
    458 (Bernoulliborg, building 5161)
  • Address:
    Nijenborgh 9
    9747 AG Groningen
    Netherlands
  • phone numbers:
    domestic: 050 363 3985
    international: +31 50 363 3985
    fax: 050 363 3800
  • e-mail: m.a.grzegorczyk@rug.nl


Curriculum Vitae

  • since 12/2013 Assistant Professor, research unit: 'Statistics and Probability', Johann Bernoulli Institute (JBI), Groningen University, Netherlands.
  • 10/2011 - 11/2013 Personal Research Grant, funded by the German Research Foundation (DFG), project title: "Development of new Bayesian network models for systems biology research" (GR3853/1-1), Department of Statistics, TU Dortmund University.
  • 04/2011 - 09/2011 Interim guest lectureship for Applied Statistics, Department of Mathematics, Carl von Ossietzky University Oldenburg.
  • 01/2011 - 03/2011 Post-doctoral research fellow, Department of Statistics, TU Dortmund University.
  • 01/2009 - 12/2010 Post-doctoral research fellow in the Graduate School 'Statistical Modelling', Department of Statistics, TU Dortmund University.
  • 07/2007 - 12/2008 Post-doctoral research fellow at the Centre for Systems Biology at Edinburgh, School of Biological Sciences, Edinburgh University, UK and Associate at Biomathematics and Statistics Scotland (BioSS), Edinburgh, Scotland, UK (7/2007-12/2011).
  • 07/2003 - 06/2007 Research Fellow (PhD student and later post-doctoral fellow) in the research projet 'Chemical Biology and Biotechnology' at the Department of Statistics, Dortmund University.


Research Interests

  • Bayesian networks and other graphical models for extracting gene-regulatory networks and protein pathways in systems biology research.


PhD students:

  • Mahdi Shafiee Kamalabad (supervised since January 2015)
  • Victor A. Bernal Arzola (DSSC project, co-supervised since July 2016)
  • Spyros Balafs (co-supervised since April 2017)


International Workshop on Statistical Modelling (IWSM) 2017

  • I was chair of the IWSM 2017 (3-7 July 2017, Groningen, Netherlands) Webpage


Associate Editorships

  • I am Associate Editor of Computational Statistics Webpage
  • I am Associate Editor of the Journal of Applied Statistics Webpage


Other involvements:

  • I participate in COST Action CA15109 (European Cooperation for Statistics of Network Data Science (COSTNET)) Webpage
  • I am member of DSSC (Data Science & System Complexity), Groningen University Webpage
  • I was awarded the 'Basis Kwalificatie Onderwijs' (University Teaching Qualification), 2017, Groningen University.
  • I was awarded a Fellowship 'Innovation of Teaching' (FIT), 2017, Groningen University.Webpage


Former Grants,

Research grant: "Development of new Bayesian network models for systems biology research" funded by German Research Foundation (DFG), 2011-2014 Webpage


Former Webpage at TU Dortmund University


Theses

  • Habilitation (Venia Legendi for Statistics), Department of Statistics, TU Dortmund University, Title of thesis: "Bayesian Networks for Reconstructing Gene Regulatory Networks in Systems Biology" (6/2012). Download PDF
  • Promotion (Dr. rer. nat.), Department of Statistics, Dortmund University, Title of doctoral thesis: "Comparative evaluation of different Graphical Models for the Analysis of Gene Expression Data." (8/2006). Download PDF
  • Diplom in Statistics with special focus on Biometrics ("Studienschwerpunkt: Biometrie"), Department of Statistics, Dortmund University, Title of Diplom thesis: "Auswertung einer Brustkrebsstudie mit logistischen Regressionsmodellen" (2/2003). Download PDF


Publications

  • Grzegorczyk, M., Aderhold, A., and Husmeier, D. (2017): Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration. Computational Statistics, 32 (2), 717-761. Available here
  • Aderhold, A., Husmeier, D., and Grzegorczyk, M. (2017): Approximate Bayesian inference in semi-mechanistic models. Statistics and Computing, 27 (4), 1003-1040. Available here
  • Grzegorczyk, M. and Shafiee Kamalabad, M. (2016): Comparative evaluation of various frequentist and Bayesian non-homogeneous Poisson counting models, Computational Statistics, 32 (1), 1-33. Available here
  • Shafiee Kamalabad, M. and Grzegorczyk, M. (2016): A non-homogeneous dynamic Bayesian network model with partially sequentially coupled network parameters. Proceedings of the International Workshop on Statistical Modelling (IWSM2016), vol. 1, 139-144, Rennes, France. Webpage IWSM2016
  • Grzegorczyk, M. (2016): A non-homogeneous dynamic Bayesian network with a hidden Markov model dependency structure among the temporal data points. Machine Learning, vol. 102 (2), 155-207. Available here
  • Grzegorczyk, M., Aderhold, A., and Husmeier, D. (2015): Network reconstruction with realistic models. In Friel and Wagner (eds.), Proceedings of the International Workshop on Statistical Modelling (IWSM2015), vol. 1, 204-209, Linz, Austria. Webpage IWSM2015
  • Grzegorczyk, M., Aderhold, A., and Husmeier, D. (2015): Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles. Statistical Applications in Genetics and Molecular Biology (SAGMB), vol. 14 (2), 143-167. Weblink
  • Aderhold, A., Husmeier, D., and Grzegorczyk, M. (2014): Statistical inference of circadian regulatory networks. Statistical Applications in Genetics and Molecular Biology (SAGMB), vol. 13 (3), 227-273. Weblink
  • Grzegorczyk, M., Aderhold, A., Smith, V.A., and Husmeier, D. (2014): Inference of circadian regulatory networks. Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) 2014, Granada, Spain, 1001-1014. Download PDF
  • Aderhold, A., Husmeier, D., Smith, A.V., Millar, A.J., and Grzegorczyk, M. (2013): Assessement of regression methods for inference of regulatory networks involved in circadian regulation. Proceedings of the Tenth International Workshop on Computational Systems Biology, WCSB 2013, Tampere, Finland, 29-33. Download Proceedings PDF
  • Grzegorczyk, M. and Husmeier, D. (2013): Regularization of Non-Homogeneous Dynamic Bayesian Networks with Global Information-Coupling based on Hierarchical Bayesian models. Machine Learning, vol. 91 (1), 105-154. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2012): Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters. Journal of Machine Learning Research (JMLR) Workshop and Conference Proceedings (AISTATS2012), 22, 467-476. Download PDF
  • Grzegorczyk, M. and Husmeier, D. (2012): A non-homogeneous dynamic Bayesian network model with sequentially coupled interaction parameters for applications in systems and synthetic biology. Statistical Applications in Genetics and Molecular Biology (SAGMB), vol. 11 (4), Article 7. Weblink
  • Grzegorczyk, M. (2012): Modelling regulatory processes during morphogenesis in Drosophila melanogaster with an improved version of the BGMD dynamic Bayesian network model. Proceedings of the Nineth International Conference on Computational Systems Biology, WCSB 2012, Ulm, Germany, 27-30. Download Proceedings PDF
  • Marbach, D., Costello J.C., Küffner, R., Vega, N.M., Prill, P.J., Camacho, D.M., Allison, K.R., The DREAM5 Consortium, Kellis, M., Collins, J.J., and Stolovitzky, G. (2012): Wisdom of crowds for robust gene network inference. Nature Methods, 9, 796-804. Weblink
  • Dondelinger, F., Aderhold, A., Lèbre, S., Grzegorczyk, M., and Husmeier, D. (2011): A Bayesian regression and multiple changepoint model for systems biology. In Conesa, D. et al. (editors) Proceedings of the 26th International Workshop on Statistical Modelling (IWSM2011), Copiformes S.L., Valencia, ISBN 978-84-694-5129-8, 189-194. Proceedings PDF
  • Husmeier, D., Werhli, A.V., and Grzegorczyk, M. (2011): Chapter 13: Advanced Applications of Bayesian networks in Systems Biology. In D.J. Balding et al. (editors): Handbook of Statistical Systems Biology, 270-289, Wiley, Chichester, UK. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2011): Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes. Bioinformatics, 27 (5), 693-699. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2011): Non-homogeneous dynamic Bayesian networks for continuous data. Machine Learning, 83 (3), 355-419. Weblink
  • Grzegorczyk, M., Husmeier, D., and Rahnenführer, J. (2011): Modelling non-stationary dynamic gene regulatory processes with the BGM model. Computational Statistics, 26 (2), 199-218. Weblink
  • Grzegorczyk, M. (2010): An Introduction to Gaussian Bayesian Networks. In: Yan Qing (Ed.): Systems Biology in Drug Discovery and Development (Springer Series: Methods and Protocols: Methods in Molecular Biology, Vol. 662). Humana Press. ISBN 978-1-60761-799-0. Weblink
  • Ickstadt, K., Bornkamp, B., Grzegorczyk, M., Wieczorek, J., Sheriff, M.R., Grecco, H.E. and Zamir, E. (2010): Nonparametric Bayesian Networks. In: Bernardo, Bayarri, Berger, Dawid, Heckerman, Smith and West (eds.): Bayesian Statistics 9, Oxford University Press, 283-316. Download PDF
  • Lohr, M., Godoy, P., Hengstler, J.G., Rahnenführer, J. and Grzegorczyk, M. (2010): In: Nykter, Ruusuvuori, Carlberg and Yli-Harja (eds.) Extracting differential regulatory sub-networks from genome-wide microarray expression data. Proceedings of the Seventh International Workshop on Computational Systems Biology, WCSB 2010, Luxembourg, 63-66. Download Proceedings PDF
  • Grzegorczyk, M., Husmeier, D. and Rahnenführer, J. (2010): Modelling Non-Stationary Gene Regulatory Processes. Advances in Bioinformatics, Volume 2010, Article ID 749848. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2009): Non-stationary continuous dynamic Bayesian networks. In Bengio, Schuurmans, Lafferty, Williams and Culotta (editors) Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems, NIPS 2009, Curran Associates, ISBN 9781605603520, 682-690. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2009): Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. In: V. Kadirkamanathan et al. (eds.): Pattern Recognition in Bioinformatics, Lecture Notes in Bioinformatics, Springer-Verlag, Berlin Heidelberg, 113-124. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2009): Modelling non-stationary gene regulatory processes with a non-homogeneous dynamic Bayesian network and the change point process. In: Manninen et al. (eds.) Proceedings of the Sixth International Workshop on Computational Systems Biology, WCSB 2009, Aarhus, Denmark, 51-54. Download Proceedings PDF
  • Grzegorczyk, M., Husmeier, D., Edwards, D.E., Ghazal, P. and Millar, A.J. (2008): Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. Bioinformatics, 24 (18), 2071-2078. Weblink
  • Grzegorczyk, M. and Husmeier, D. (2008): Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. Machine Learning, 71 (2-3), 265-305. Weblink
  • Grzegorczyk, M. (2008): Comparison of two different stochastic models for extracting protein regulatory pathways with Bayesian networks. Journal of Toxicology and Environmental Health, Part A, 71, 780–787. Weblink
  • Grzegorczyk, M., Husmeier, D. and Werhli, A.V. (2008) Reverse Engineering Gene Regulatory Networks with various Machine Learning Methods. In Emmert-Streib and Dehmer (eds.) Analysis of Microarray Data. A Network-Based Approach, Wiley-WCH. Weblink
  • Grzegorczyk, M. (2007): Extracting protein regulatory networks with graphical models. Proteomics, 7, 51-59. Weblink
  • Urfer, W., Grzegorczyk, M. and Jung, K. (2006): Statistics for Proteomics: A review of tools for analyzing experimental data. Proteomics, 6, 48-55. Weblink
  • Werhli, A.V., Grzegorczyk, M. and Husmeier, D. (2006): Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical Gaussian models and Bayesian networks. Bioinformatics, 22 (20), 2523-2531. Weblink
  • Sievers, S., Fritsch, C., Grzegorczyk, M., Kuhnen, C. and Müller, O. (2006): Absolute ß-catenin concentrations in Wnt pathway stimulated and non-stimulated cells. Biomarkers, 11 (3), 270-278. Weblink
  • Werhli, A.V., Grzegorczyk, M., Chiang, M.T. and Husmeier, D. (2006): Improved Gibbs sampling for detecting mosaic structures in DNA sequence alignments In: Urfer and Turkman (eds.) Statistics in Genomics and Proteomics, Centro Internacional de Matematica, Coimbra. [no link]
  • Kutzner, N., Hoffmann, I., Linke, C., Thienel, T., Grzegorczyk, M., Urfer, W., Martin, D., Winde, G., Traska, T., Hohlbach, G., Müller, K.-M., Kuhnen, C. and Müller, O. (2005): Non-invasive detection of colorectal tumours by the combined application of molecular diagnosis and the faecal occult blood test. Cancer Letters, 1, 33-41. Weblink


Teaching at Groningen University (since December 2013)

  • Honour College (on Bayesian networks) [2016/2017]
  • Contemporary Statistics [2016/2017]
  • Linear Algebra and Multivariable Calculus for IEM [2016/2017]
  • Statistical Reasoning [2016/2017]
  • Honours College (on Bayesian networks) [2015/2016]
  • Linear Algebra and Multivariable Calculus for IEM [2015/2016]
  • Statistical Genomics [2015/2016]
  • Statistical Reasoning [2015/2016]
  • Contemporary Statistics [2014/2015]
  • Statistical Reasoning [2014/2015]
  • Honours College (on Graphical Models) [2013/2014]


Supervised Master and Bachelor projects at Groningen University

  • Klaas-Daniel Sijtsma (2007): Bayesian Changepoint Models. BSc thesis: Mathematics, Groningen University.
  • Dagmar Heeg (2017): Optimization of the Bayesian Poisson Changepoint Model. BSc thesis: Mathematics, Groningen University.
  • Dennis Steenhuis (2017): On the Comparison of Changepoints Models in Network Reconstruction with Themselves and their Bayesian Counterparts. MSc thesis: Mathematics, Groningen University.
  • Gerard Hekkelman (2017): Comparing Graphical Models with Pseudo-likelihood Methods and their Bayesian Counterparts on Gene Regulatory Networks. MSc thesis: Mathematics, Groningen University.
  • Martin Eisenmann (2016): Statistical Support of Ageing Research at the UMCG. MSc thesis: Mathematics, Groningen University.
  • Samuel Toby Knight (2015): An Inhomogeneous Bayesian Poisson-Gamma Model for Taxi Calls in New York City. BSc thesis: Econometrics and Operational Research, Groningen University.


Presentations (since December 2013)

  • 32nd International Workshop on Statistical Modelling (IWSM), (Groningen, Netherlands, 3-7 July 2017) Weblink
  • ICMS workshop: 'Learning graphical models in high dimensional settings' (Edinburgh, UK, 4-7 April, 2017) Weblink
  • Workshop on Computational Models in Biology and Medicine (Hannover, Germany, 2-3 March 2017) Webpage
  • Statistics for Structures Seminar Series (Amsterdam, Netherlands, 4 November 2016) Weblink
  • 13th Applied Statistics, International Conference (Ribno (Bled), Solovenia, 18-21 September 2016) Short Course on Bayesian networks Weblink
  • 31st International Workshop on Statistical Modelling (IWSM), (Rennes, France, 4-8 July 2016) Weblink
  • 30th International Workshop on Statistical Modelling (IWSM), (Linz, Austria, 6-10 July 2015) Weblink
  • Satelite meeting: 'Inferring dynamic genetic networks', International Biometric Society (IBS) Channel Network Conference (Nijmegen, Netherlands, 20-22 April 2015) Weblink
  • Van Dantzig Seminar Lecture Series (Amsterdam, Netherlands, 9 October 2014) Weblink
  • International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO), (Granada, Spain, 7-9 April 2014) Weblink