PD Dr. rer. nat. habil. Dörte Wittenburg

Research Institute for Farm Animal Biology (FBN)
Head of the focus topic "Promoting diversity in animal farming"
Head of Working group Statistics in Genomics
Wilhelm-Stahl-Allee 2
18196 Dummerstorf

Research interests

  • Statistical methods for the estimation of genetic effects on quantitative traits
  • Inclusion of dependencies between genomic sites in penalised regression approaches
  • Estimation of population-genetic parameters (linkage disequilibrium and recombination rate)

Curriculum Vitae

  • 2021: Habilitation and Venia Legendi in animal breeding and genetics
    Thesis: Statistical perspectives on dependencies between genomic markers
  • Since 2019: Head of Research Group “Statistics in Genomics”, FBN Dummerstorf
  • 2013-2018: Head of Junior Scientist Group “Improving the genome-based phenotype prediction”, FBN Dummerstorf
  • 2008-2012: Postdoc in Junior Scientist Group “BovIBI Bovine Integrative Bioinformatics for Genomic Selection”, FBN Dummerstorf
  • 2005-2008: Doctoral studies in statistical genetics (Dr. rer. nat. in Biomathematics), FBN Dummerstorf and University Greifswald
    PhD thesis: Statistical modelling of birth weight variability within litter in pigs
  • 2000-2005: Studies of Business Mathematics (Dipl.-Math. oec.), University Rostock
    Diploma thesis: Linear and generalised linear models for the detection of QTL effects on the variability of repeated measurements


Contribution to lectures in the module “Statistical modelling and experimental design” which is part of the master programme Sustainable Agricultural Systems at the University Rostock, AUF

Master theses offered in the field of animal breeding at https://www.auf.uni-rostock.de/studium/studienorganisation/angebot-abschlussarbeiten/


Klosa, J.; Simon, N.; Liebscher, V.; Wittenburg, D. (2023):
A fitted sparse-group lasso for genome-based evaluations. IEEE ACM T COMPUT BI 20 (1): 30-38
Melzer, N.; Qanbari, S.; Ding, X.; Wittenburg, D. (2023):
CLARITY: a Shiny app for interactive visualisation of the bovine physical-genetic map. Front Genet 14: 1082782, 1-10
Jahnel, R. E.; Blunk, I.; Wittenburg, D.; Reinsch, N. (2023):
Relationship between milk urea content and important milk traits in Holstein cattle. Animal 17 (5): 100767, 1-10
Piepho, H.P.; Gabriel, D.; Hartung, J.; Büchse, A.; Grosse, M.; Kurz, S.; Laidig, F.; Michel, V.; Proctor, I.; Sedlmeier, J.E.; Toppel, K.; Wittenburg, D. (2022):
One, two, three: portable sample size in agricultural research. J AGR SCI-CAMBRIDGE 160 (6): 459-482
Qanbari, S.; Schnabel, R. D.; Wittenburg, D. (2022):
Evidence of Rare Misassemblies in the Bovine Reference Genome Revealed by Population Genetic Metrics. Anim Genet 53 (4): 498-505
de los Rios Pérez, L.; Druet, T.; Goldammer, T.; Wittenburg, D. (2022):
Analysis of autozygosity using whole-genome sequence data of full-sib families in pikeperch (Sander lucioperca). Front Genet 12: 786934, 1-9
Wittenburg, D. (2021):
Statistical perspectives on dependencies between genomic markers Rostock: 1-161
Goldammer, T.; Verleih, M.; Brunner, R. M.; Rebl, A.; Nguinkal, J. A.; de los Rios Pérez, L.; Schäfer, N.; Stüecken, M.; Swirplies, F.; Wittenburg, D. (2021):
Pikeperch genome data – basis for the smart farming in aquaculture. Mitteilungen der Landesforschungsanstalt für Landw (63): 125-133
Jahnel, R. E.; Wittenburg, D.; Mayer, M.; Täubert, H.; Reinsch, N. (2021):
DGFZ Preis 2020 (Masterarbeiten) Estimation of genetic parameters of milk urea content. Zuchtungskunde 93 (2): 157-168
Wittenburg, D.; Doschoris, M.; Klosa, J. (2021):
Grouping of genomic markers in populations with family structure. BMC Bioinformatics 22: 79, 1-12
de los Rios Pérez, L.; Nguinkal, J. A.; Verleih, M.; Rebl, A.; Brunner, R. M.; Klosa, J.; Schäfer, N.; Stüeken, M.; Goldammer, T.; Wittenburg, D. (2020):
An ultra-high density SNP-based linkage map for enhancing the pikeperch (Sander lucioperca) genome assembly to chromosome-scale. Sci Rep-UK 10 (22335): 1-13
Qanbari, S.; Wittenburg, D. (2020):
Male recombination map of the autosomal genome in German Holstein. Genet Sel Evol 52: 73, 1-11
Klosa, J.; Simon, N.; Westermark, P. O.; Liebscher, V.; Wittenburg, D. (2020):
Seagull: lasso, group lasso and sparse-group lasso regularisation for linear regression models via proximal gradient descent. BMC Bioinformatics 21: 407, 1-8
de los Rios Pérez, L.; Brunner, R. M.; Hadlich, F.; Rebl, A.; Kühn, C.; Wittenburg, D.; Goldammer, T.; Verleih, M. (2020):
Comparative analysis of the transcriptome and distribution of putative SNPs in two rainbow trout (Oncorhynchus mykiss) breeding strains by using next-generation sequencing. Genes-Basel 11: 841, 1-16
Wittenburg, D.; Bonk, S. M.; Doschoris, M.; Reyer, H. (2020):
Design of experiments for fine-mapping quantitative trait loci in livestock populations . BMC Genet 21: 66,1-14
Nguinkal, J. A.; Brunner, R. M.; Verleih, M.; Rebl, A.; de los Rios Pérez, L.; Schäfer, N.; Hadlich, F.; Stüeken, M.; Wittenburg, D.; Goldammer, T. (2019):
The first highly contiguous genome assembly of pikeperch (Sander lucioperca), an emerging aquaculture species in Europe. Genes-Basel 10: 708, 1-14
Reyer, H.; Oster, M.; Wittenburg, D.; Murani, E.; Ponsuksili, S.; Wimmers, K. (2019):
Genetic contribution to variation in blood calcium, phosphorus, and alkaline phosphatase activity in pigs. Front Genet 10: 590, 1-12
Wittenburg, D.; Liebscher, V. (2018):
An approximate Bayesian significance test for genomic evaluations. Biometrical J 60: 1096-1109
Boerner, V.; Wittenburg, D. (2018):
On estimation of genome composition in genetically admixed individuals using constrained genomic regression. Front Genet 9: 185, 1-14
Hampel, A.; Teuscher, F.; Gomez-Raya, L.; Doschoris, M.; Wittenburg, D. (2018):
Estimation of recombination rate and maternal linkage disequilibrium in half-sibs. Front Genet 9: 186, 1-13