Ralf Eggeling
Ralf Eggeling
Postdoctoral researcher, University of Tübingen
Verified email at - Homepage
Cited by
Cited by
Kinetics and correlates of the neutralizing antibody response to SARS-CoV-2 infection in humans
K Vanshylla, V Di Cristanziano, F Kleipass, F Dewald, P Schommers, ...
Cell Host & Microbe, 2021
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
Evaluation of a rapid antigen test to detect SARS-CoV-2 infection and identify potentially infectious individuals
M Korenkov, N Poopalasingam, M Madler, K Vanshylla, R Eggeling, ...
Journal of clinical microbiology 59 (9), e00896-21, 2021
Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data
R Eggeling, T Roos, P Myllymäki, I Grosse
BMC bioinformatics 16, 1-15, 2015
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
Durability of omicron-neutralising serum activity after mRNA booster immunisation in older adults
K Vanshylla, P Tober-Lau, H Gruell, F Münn, R Eggeling, N Pfeifer, NH Le, ...
The Lancet Infectious Diseases 22 (4), 445-446, 2022
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
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
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
Robust learning of inhomogeneous PMMs
R Eggeling, T Roos, P Myllymäki, I Grosse
Artificial Intelligence and Statistics, 229-237, 2014
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
Disentangling transcription factor binding site complexity
R Eggeling
Nucleic acids research 46 (20), e121-e121, 2018
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
Inhomogeneous parsimonious Markov models
R Eggeling, A Gohr, PY Bourguignon, E Wingender, I Grosse
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013
Dealing with Small Data: On the Generalization of Context Trees
R Eggeling, M Koivisto, I Grosse
International Conference on Machine Learning (ICML), 2015
DNA-binding properties of the MADS-domain transcription factor SEPALLATA3 and mutant variants characterized by SELEX-seq
S Käppel, R Eggeling, F Rümpler, M Groth, R Melzer, G Theißen
Plant Molecular Biology 105, 543-557, 2021
Pruning Rules for Learning Parsimonious Context Trees
R Eggeling, M Koivisto
32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016
Finding Optimal Bayesian Networks with Local Structure
T Talvitie, R Eggeling, M Koivisto
International Conference on Probabilistic Graphical Models, 451-462, 2018
Respiratory viruses dynamics and interactions: ten years of surveillance in central Europe
G Horemheb-Rubio, R Eggeling, N Schmeiβer, N Pfeifer, T Lengauer, ...
BMC Public Health 22 (1), 1-10, 2022
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
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