Ralf Eggeling
Ralf Eggeling
Postdoctoral researcher, University of Tübingen
Geverifieerd e-mailadres voor informatik.uni-tuebingen.de - Homepage
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Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data
R Eggeling, T Roos, P Myllymäki, I Grosse
BMC bioinformatics 16 (1), 375, 2015
312015
On the value of intra-motif dependencies of human insulator protein CTCF
R Eggeling, A Gohr, J Keilwagen, M Mohr, S Posch, AD Smith, I Grosse
PLoS One 9 (1), 2014
222014
Polyclonal and convergent antibody response to Ebola virus vaccine rVSV-ZEBOV
SA Ehrhardt, M Zehner, V Krähling, H Cohen-Dvashi, C Kreer, N Elad, ...
Nature medicine 25 (10), 1589-1600, 2019
212019
Robust learning of inhomogeneous PMMs
R Eggeling, T Roos, P Myllymäki, I Grosse
Artificial Intelligence and Statistics, 229-237, 2014
132014
Inhomogeneous parsimonious Markov models
R Eggeling, A Gohr, PY Bourguignon, E Wingender, I Grosse
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013
112013
InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites
R Eggeling, I Grosse, J Grau
Bioinformatics 33 (4), 580-582, 2017
102017
Dealing with Small Data: On the Generalization of Context Trees
R Eggeling, M Koivisto, I Grosse
International Conference on Machine Learning (ICML), 2015
82015
Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth
J Viinikka, R Eggeling, M Koivisto
International Conference on Artificial Intelligence and Statistics, 1570-1578, 2018
72018
Learning Bayesian networks with local structure, mixed variables, and exact algorithms
T Talvitie, R Eggeling, M Koivisto
International Journal of Approximate Reasoning 115, 69-95, 2019
52019
Pruning Rules for Learning Parsimonious Context Trees
R Eggeling, M Koivisto
32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016
52016
Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data
L Handl, A Jalali, M Scherer, R Eggeling, N Pfeifer
Bioinformatics 35 (14), i154-i163, 2019
42019
Finding Optimal Bayesian Networks with Local Structure
T Talvitie, R Eggeling, M Koivisto
International Conference on Probabilistic Graphical Models, 451-462, 2018
32018
Disentangling transcription factor binding site complexity
R Eggeling
Nucleic acids research 46 (20), e121-e121, 2018
32018
Gibbs sampling for parsimonious Markov models with latent variables
R Eggeling, PY Bourguignon, A Gohr, I Grosse
The sixth European workshop on probabilistic graphical models, 2012
32012
On Structure Priors for Learning Bayesian Networks
R Eggeling, J Viinikka, A Vuoksenmaa, M Koivisto
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
22019
Extended Sunflower Hidden Markov Models for the recognition of homotypic cis-regulatory modules
IM Lemnian, R Eggeling, I Grosse
German Conference on Bioinformatics 2013, 2013
22013
Evolution of the AMP-Activated Protein Kinase Controlled Gene Regulatory Network
C Mehlgarten, R Eggeling, A Gohr, M Bönn, I Lemnian, M Nettling, ...
Information-and Communication Theory in Molecular Biology, 211-238, 2018
12018
Model selection in a setting with latent variables
R Eggeling, T Roos, P Myllymäki, I Grosse
Proc. 6th Workshop on Information Theoretic Methods in Science and …, 2013
12013
Comparison of NML and Bayesian scoring criteria for learning parsimonious Markov models
R Eggeling, TT Roos, P Myllymäki, I Grosse
Proceedings of the 5th Workshop on Information Theoretic Methods in Science …, 2012
12012
Algorithms for learning parsimonious context trees
R Eggeling, I Grosse, M Koivisto
Machine Learning 108 (6), 879-911, 2019
2019
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Artikelen 1–20