Search the dblp DataBase

Publications of Author

1. Dirk Husmeier
   Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models. [Citation Graph (0, 0)][DBLP]
   ECCB/JBI, 2005, pp:172- [Conf]
   
2. Dirk Husmeier, Frank Wright
   Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models. [Citation Graph (0, 0)][DBLP]
   German Conference on Bioinformatics, 2000, pp:19-26 [Conf]
   
3. Dirk Husmeier, Frank Wright
   Approximate Bayesian Discrimination between Alternative DNA Mosaic Structures. [Citation Graph (0, 0)][DBLP]
   German Conference on Bioinformatics, 2001, pp:182-184 [Conf]
   
4. Dirk Husmeier, John G. Taylor
   Modeling Conditional Probabilities with Committees of RVFL Networks. [Citation Graph (0, 0)][DBLP]
   ICANN, 1997, pp:1053-1058 [Conf]
   
5. Dirk Husmeier, Gráinne McGuire
   Detecting recombination with MCMC. [Citation Graph (0, 0)][DBLP]
   ISMB, 2002, pp:345-353 [Conf]
   
6. Dirk Husmeier, Frank Wright
   Probabilistic divergence measures for detecting interspecies recombination. [Citation Graph (0, 0)][DBLP]
   ISMB (Supplement of Bioinformatics), 2001, pp:123-131 [Conf]
   
7. Dirk Husmeier
   Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. [Citation Graph (0, 0)][DBLP]
   Bioinformatics, 2003, v:19, n:17, pp:2271-2282 [Journal]
   
8. Dirk Husmeier, Frank Wright
   A Bayesian approach to discriminate between alternative DNA sequence segmentations. [Citation Graph (0, 0)][DBLP]
   Bioinformatics, 2002, v:18, n:2, pp:226-234 [Journal]
   
9. Dirk Husmeier, Frank Wright, Iain Milne
   Detecting interspecific recombination with a pruned probabilistic divergence measure. [Citation Graph (0, 0)][DBLP]
   Bioinformatics, 2005, v:21, n:9, pp:1797-1806 [Journal]
   
10. Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
    A regularized discriminative model for the prediction of protein-peptide interactions. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:5, pp:532-540 [Journal]
    
11. 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. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:11, pp:1806-1807 [Journal]
    
12. Adriano V. Werhli, Marco Grzegorczyk, Dirk Husmeier
    Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:20, pp:2523-2531 [Journal]
    
13. Kaspar Althoefer, Bart Krekelberg, Dirk Husmeier, Lakmal D. Seneviratne
    Reinforcement learning in a rule-based navigator for robotic manipulators. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2001, v:37, n:1-4, pp:51-70 [Journal]
    
14. Dirk Husmeier, Frank Wright
    Detection of Recombination in DNA Multiple Alignments with Hidden Markov Models. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:8, n:4, pp:401-427 [Journal]
    
15. Dirk Husmeier
    The Bayesian Evidence Scheme for Regularizing Probability-Density Estimating Neural Networks. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:11, pp:2685-2717 [Journal]
    
16. Dirk Husmeier
    Learning non-stationary conditional probability distributions. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2000, v:13, n:3, pp:287-290 [Journal]
    
17. Dirk Husmeier, William D. Penny, Stephen J. Roberts
    An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1999, v:12, n:4-5, pp:677-705 [Journal]
    
18. Dirk Husmeier, John G. Taylor
    Predicting Conditional Probability Densities of Stationary Stochastic Time Series. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:3, pp:479-497 [Journal]
    
19. Dirk Husmeier, John G. Taylor
    Neural Networks for Predicting Conditional Probability Densities: Improved Training Scheme Combining EM and RVFL. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1998, v:11, n:1, pp:89-116 [Journal]
    
20. Stephen J. Roberts, Dirk Husmeier, Iead Rezek, William D. Penny
    Bayesian Approaches to Gaussian Mixture Modeling. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Pattern Anal. Mach. Intell., 1998, v:20, n:11, pp:1133-1142 [Journal]
    
21. Wolfgang P. Lehrach, Dirk Husmeier, Christopher K. I. Williams
    Probabilistic in Silico Prediction of Protein-Peptide Interactions. [Citation Graph (0, 0)][DBLP]
    Systems Biology and Regulatory Genomics, 2005, pp:188-197 [Conf]
    
22. 
    Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing. [Citation Graph (, )][DBLP]
    
    
23. 
    Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. [Citation Graph (, )][DBLP]
    
    
24. 
    Distinguishing Regional from Within-Codon Rate Heterogeneity in DNA Sequence Alignments. [Citation Graph (, )][DBLP]
    
    
25. 
    Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. [Citation Graph (, )][DBLP]
    
    
26. 
    TOPALi v2: a rich graphical interface for evolutionary analyses of multiple alignments on HPC clusters and multi-core desktops. [Citation Graph (, )][DBLP]