Dirk Husmeier

	2012
37		Marco Grzegorczyk, Dirk Husmeier: Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters. Journal of Machine Learning Research - Proceedings Track 22: 467-476 (2012)
	2011
36		Marco Grzegorczyk, Dirk Husmeier: Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes. Bioinformatics 27(5): 693-699 (2011)
35		Marco Grzegorczyk, Dirk Husmeier: Non-homogeneous dynamic Bayesian networks for continuous data. Machine Learning 83(3): 355-419 (2011)
	2010
34		Frank Dondelinger, Sophie Lebre, Dirk Husmeier: Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing. ICML 2010: 303-310
33		Dirk Husmeier, Frank Dondelinger, Sophie Lebre: Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks. NIPS 2010: 901-909
32		Marco Grzegorczyk, Dirk Husmeier, Jörg Rahnenführer: Modelling Nonstationary Gene Regulatory Processes. Adv. Bioinformatics 2010: (2010)
31		Ali Faisal, Frank Dondelinger, Dirk Husmeier, Colin M. Beale: Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods. Ecological Informatics 5(6): 451-464 (2010)
	2009
30		Marco Grzegorczyk, Dirk Husmeier: Non-stationary continuous dynamic Bayesian networks. NIPS 2009: 682-690
29		Marco Grzegorczyk, Dirk Husmeier: Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. PRIB 2009: 113-124
28		Alexander V. Mantzaris, Dirk Husmeier: Distinguishing Regional from Within-Codon Rate Heterogeneity in DNA Sequence Alignments. PRIB 2009: 187-198
27		Iain Milne, Dominik Lindner, Micha Bayer, Dirk Husmeier, Gráinne McGuire, David F. Marshall, Frank Wright: TOPALi v2: a rich graphical interface for evolutionary analyses of multiple alignments on HPC clusters and multi-core desktops. Bioinformatics 25(1): 126-127 (2009)
26		Kuang Lin, Dirk Husmeier: Modelling Transcriptional Regulation with a Mixture of Factor Analyzers and Variational Bayesian Expectation Maximization. EURASIP J. Bioinformatics and Systems Biology 2009: (2009)
	2008
25		Marco Grzegorczyk, Dirk Husmeier, Kieron D. Edwards, Peter Ghazal, Andrew J. Millar: Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. Bioinformatics 24(18): 2071-2078 (2008)
24		Adriano Velasque Werhli, Dirk Husmeier: Gene Regulatory Network Reconstruction by Bayesian Integration of Prior Knowledge and/or Different Experimental Conditions. J. Bioinformatics and Computational Biology 6(3): 543-572 (2008)
23		Marco Grzegorczyk, Dirk Husmeier: Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. Machine Learning 71(2-3): 265-305 (2008)
	2006
22		Adriano Velasque Werhli, Marco Grzegorczyk, Dirk Husmeier: Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. Bioinformatics 22(20): 2523-2531 (2006)
21		Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams: A regularized discriminative model for the prediction of protein-peptide interactions. Bioinformatics 22(5): 532-540 (2006)
	2005
20		Dirk Husmeier: Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models. ECCB/JBI 2005: 172
19		Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams: Probabilistic in Silico Prediction of Protein-Peptide Interactions. Systems Biology and Regulatory Genomics 2005: 188-197
18		Dirk Husmeier, Frank Wright, Iain Milne: Detecting interspecific recombination with a pruned probabilistic divergence measure. Bioinformatics 21(9): 1797-1806 (2005)
	2004
17		Iain Milne, Frank Wright, Glenn Rowe, David F. Marshall, Dirk Husmeier, Gráinne McGuire: TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments. Bioinformatics 20(11): 1806-1807 (2004)
	2003
16		Dirk Husmeier: Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. Bioinformatics 19(17): 2271-2282 (2003)
	2002
15		Dirk Husmeier, Gráinne McGuire: Detecting recombination with MCMC. ISMB 2002: 345-353
14		Dirk Husmeier, Frank Wright: A Bayesian approach to discriminate between alternative DNA sequence segmentations. Bioinformatics 18(2): 226-234 (2002)
13		Dirk Husmeier, Frank Wright: Detection of Recombination in DNA Multiple Alignments with Hidden Markov Models. Journal of Computational Biology 8(4): 401-427 (2002)
	2001
12		Dirk Husmeier, Frank Wright: Approximate Bayesian Discrimination between Alternative DNA Mosaic Structures. German Conference on Bioinformatics 2001: 182-184
11		Dirk Husmeier, Frank Wright: Probabilistic divergence measures for detecting interspecies recombination. ISMB (Supplement of Bioinformatics) 2001: 123-131
10		Kaspar Althoefer, Bart Krekelberg, Dirk Husmeier, Lakmal D. Seneviratne: Reinforcement learning in a rule-based navigator for robotic manipulators. Neurocomputing 37(1-4): 51-70 (2001)
	2000
9		Dirk Husmeier, Frank Wright: Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models. German Conference on Bioinformatics 2000: 19-26
8		Dirk Husmeier: The Bayesian Evidence Scheme for Regularizing Probability-Density Estimating Neural Networks. Neural Computation 12(11): 2685-2717 (2000)
7		Dirk Husmeier: Learning non-stationary conditional probability distributions. Neural Networks 13(3): 287-290 (2000)
	1999
6		Dirk Husmeier: Neural networks for conditional probability estimation - forecasting beyond point predictions. Springer 1999: I-XXIII, 1-275
5		Dirk Husmeier, William D. Penny, Stephen J. Roberts: An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. Neural Networks 12(4-5): 677-705 (1999)
	1998
4		Stephen J. Roberts, Dirk Husmeier, Iead Rezek, William D. Penny: Bayesian Approaches to Gaussian Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 20(11): 1133-1142 (1998)
3		Dirk Husmeier, John G. Taylor: Neural Networks for Predicting Conditional Probability Densities: Improved Training Scheme Combining EM and RVFL. Neural Networks 11(1): 89-116 (1998)
	1997
2		Dirk Husmeier, John G. Taylor: Modeling Conditional Probabilities with Committees of RVFL Networks. ICANN 1997: 1053-1058
1		Dirk Husmeier, John G. Taylor: Predicting Conditional Probability Densities of Stationary Stochastic Time Series. Neural Networks 10(3): 479-497 (1997)

Coauthor Index

1	Kaspar Althoefer	[10]
2	Micha Bayer (M. M. Bayer)	[27]
3	Colin M. Beale	[31]
4	Frank Dondelinger	[31] [33] [34]
5	Kieron D. Edwards	[25]
6	Ali Faisal	[31]
7	Peter Ghazal	[25]
8	Marco Grzegorczyk	[22] [23] [25] [29] [30] [32] [35] [36] [37]
9	Bart Krekelberg	[10]
10	Sophie Lebre	[33] [34]
11	Wolfgang P. Lehrach	[19] [21]
12	Kuang Lin	[26]
13	Dominik Lindner	[27]
14	Alexander V. Mantzaris	[28]
15	David F. Marshall	[17] [27]
16	Gráinne McGuire	[15] [17] [27]
17	Andrew J. Millar	[25]
18	Iain Milne	[17] [18] [27]
19	William D. Penny (Will D. Penny)	[4] [5]
20	Jörg Rahnenführer	[32]
21	Iead Rezek	[4]
22	Stephen J. Roberts	[4] [5]
23	Glenn Rowe	[17]
24	Lakmal D. Seneviratne	[10]
25	John G. Taylor	[1] [2] [3]
26	Adriano Velasque Werhli	[22] [24]
27	Christopher K. I. Williams	[19] [21]
28	Frank Wright	[9] [11] [12] [13] [14] [17] [18] [27]

Colors in the list of coauthors

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