Dr.-Ing. Nina Melzer

Research Institute for Farm Animal Biology (FBN)
working group Chronobiology & Computational Biology
Wilhelm-Stahl-Allee 2
18196 Dummerstorf

Research interests

  • Statistical learning methods
  • Modeling of the Genotype-Phenotype Map
  • Quantitative genetics
  • animal social behavior

Curriculum Vitae

  • 2020-present: Senior scientist at the Leibniz Institute for Farm Animal Biology (FBN) Dummerstorf, Institute of Genetics and Biometry, Statistics in Genomics Unit
  • 2016-2020: Leader of Junior Research Group “Phenotyping of Animal Welfare”, Leibniz Institute for Farm Animal Biology (FBN) Dummerstorf, Institute of Genetics and Biometry, Livestock Genetics and Breeding Unit. The junior research group was part of the Phenomics Joint Project “PHÄNOMICS” and was funded by the BMBF (Grant No.: 0315536G) and by the FBN.
  • 2016: Three-month research stay at the University of Guelph, Department of Animal Biosciences, Canada (Topic: "Analysis of genomic inbreeding in dairy cattle using Next-Generation Sequencing (NGS)"; funded by the DFG (Grant No.: ME 4746/1-1) and FBN)
  • 2013-2015: PostDoc at the Leibniz Institute for Farm Animal Biology (FBN) Dummerstorf, Institute of Genetics and Biometry
  • 2014: Engineering Doctorate, Dr.-Ing. (Bioinformatics). Thesis: "Investigating possibilities to predict milk phenotypes in Holstein Friesian cows based on a more complex model of the genotype-phenotype map" at the University Rostock, Germany
  • 2010: Research assistant at the University of Rostock, Institute of Computer Science
  • 2008-2013: PhD student at the Leibniz Institute for Farm Animal Biology (FBN) Dummerstorf, Institute of Genetics and Biometry
  • 2006: Diploma in Bioinformatics. Topic: "Differentielle Korrelation von Mikroarray-Daten"/"Differential correlation of microarray data" at the Martin-Luther University Halle-Wittenberg, Halle (Saale), Germany

Publications

Melzer, N.; Wittenburg, D.; Repsilber, D. (2013):
Investigating a complex genotype-phenotype map for development of methods to predict genetic values based on genome-wide marker data - a simulation study for the livestock perspective. Arch Tierzucht 56 (38): 380-398
https://dx.doi.org/10.7482/0003-9438-56-038
Melzer, N.; Wittenburg, D.; Repsilber, D. (2013):
Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows. Plos One 8 (8): 1-10
https://dx.doi.org/10.1371/journal.pone.0070256
Melzer, N.; Wittenburg, D.; Hartwig, S.; Jakubowski, S.; Kesting, U.; Willmitzer, L.; Lisec, J.; Reinsch, N.; Repsilber, D. (2013):
Investigating associations between milk metabolite profiles and milk traits of Holstein cows. J Dairy Sci 96 (3): 1521-1534
https://dx.doi.org/10.3168/jds.2012-5743
Wittenburg, D.; Melzer, N.; Willmitzer, L.; Lisec, J.; Kesting, U.; Reinsch, N.; Repsilber, D. (2013):
Milk metabolites and their genetic variability. J Dairy Sci 96 (4): 2557-2569
https://dx.doi.org/10.3168/jds.2012-5635
Wittenburg, D.; Melzer, N.; Reinsch, N. (2011):
Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers. BMC Genet 12: 74-88
https://dx.doi.org/10.1186/1471-2156-12-74