Prof. Dr. Klaus Jung
© Klaus Jung

Group Head, Genomics and Bioinformatics of Infectious Diseases

Institute for Animal Breeding and Genetics

University of Veterinary Medicine Hannover, Foundation
Bünteweg 17p
D-30559 Hannover

Telefon:+49 511 953-8878
Fax: +49 511 953-8582

E-Mail: klaus.jung(at)

Curriculum vitae

Since 2015:
Professor for Genomics and Bioinformatics of Infectious Diseases, Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover

Habilitation (venia legendi: medical biometry and statistical bioinformatics), Georg-August-University Göttingen

Head of the Core Facility Medical Biometry and Statistical Bioinformatics, University Medical Center Göttingen

Postdoctoral Research Fellow, from 2013 Privatdozent, Department of Medical Statistics, University Medical Center Göttingen

Postdoctoral Research Fellow, Medical Proteom Center, Ruhr-University Bochum

Dr. rer. nat., University of Dortmund

Doctoral student at the Graduate School 'Statistical Modelling', University of Dortmund

Studies of statistics with minor subject biology, University of Dortmund

Born in Wiesbaden

Research interests

The research of Prof. Jung concentrates on the development of computational methods and tools for the analysis of `Omics' data, with a special focus on data from infection research. For further details on the research projects see the homepage of the group Genomics and Bioinformatics of Infectious Diseases.

Publications and Software

Selected peer-reviewed articles on bioinformatics methods

  • Krepel J, Kircher M, Kohls M and Jung K (2021) Comparison of merging strategies for builidng machine learning models on multiple independent gene expression data sets. Statistical Analysis and Data Mining, online first. [open acces]
  • Kohls M, Saremi B, Muchsin I, Fischer N, Becher P and Jung K (2021) A resampling strategy for studying robustness in virus detection pipelines. Computational Biology and Chemistry, 94, 107555. [abstract, R-code virDisco2]
  • Saremi B, Kohls M, Liebig P, Siebert U and Jung K (2021) Measuring Reproducibility of Virus Meta-Genomics Analyses using Bootstrap Samples from FASTQ-Files. Bioinformatics, 37(8), 1068-1075. [abstract, Phyton-code RESEQ]
  • Winter C, Kosch R, Ludlow M, Osterhaus A and Jung K (2019) Network Meta-Analysis Correlates with Analysis of Merged Independent Transcriptome Expression Data. BMC Bioinformatics, 20(1): 144. [open access, R-code for network meta-analysis]
  • Kosch R and Jung K (2018) Conducting Gene Set Tests in Meta-Analyses of Transcriptome Expression Data. Research Synthesis Methods, 10, 99-112. [open access]
  • Kruppa J, Jo WK, van der Vries E, Ludlow M, Osterhaus A, Baumgärtner W and Jung K (2018) Virus detection in high-throughput sequencing data without reference genome of the host. Infection, Genetics and Evolution, 66, 180-187. [abstract, R-code virDisco]
  • Kruppa J, Lepenies B, Jung K (2018) A genetic algorithm for simulating correlated binary data from biomedical research. Computers in Biology and Medicine, 92, 1-8. [abtract, R-package RepeatedHighDim]
  • Kruppa J, van der Vries E, Jo WK, Postel A, Becher P, Osterhaus A, Jung K (2017) kmerPyramid: an interactive visualization tool for nucleobase and k-mer frequencies. Bioinformatics, 33, 3115-3116. [open access, R-package kmerPyramid]
  • Kruppa J and Jung K (2017) Automated multigroup outlier identification in molecular high-throughput data using bagplots and gemplots. BMC Bioinformatics, 18: 232. [open access, R-package gemPlot]
  • Kruppa J, Kramer F, Beißbarth T and Jung K (2016): A simulation framework for correlated count data of feature subsets in high-throughput sequencing or proteomics experiments. Sta-tistical Applications in Genetics and Molecular Biology, 15, 143-156. [open access]
  • Bayerlová M, Jung K, Kramer K, Klemm F, Bleckmann A, Beißbarth T (2015) Comparative study on gene set and pathway topology-based enrichment methods. BMC Bioinformatics, 16:334. [open access]
  • Jung K, Dihazi H, Bibi A, Dihazi GH and Beißbarth T (2014): Adaption of the Global Test Idea to Proteomics Data with Missing Values. Bioinformatics, 30, 1424-1430. [open access, R-package RepeatedHighDim]
  • Leha A, Jung K and Beißbarth T (2013): Utilization of ordinal response structures in classifi-cation with high-dimensional expression data. Proceedings of the German Conference on Bioinformatics 2013, 90-100. [pdf]
  • Fuchs M, Beißbarth T Wingender E and Jung K (2013): Connecting high-dimensional mRNA and miRNA expression data for binary medical classification problems. Computer Methods and Programs in Biomedicine, 111, 592-601. [open access]
  • Artmann S, Jung K, Bleckmann A and Beißbarth T (2012): Detection of simultaneous Group Effects in microRNA Expression and related Target Gene Sets. PloS ONE, 7, e38365. [open access]
  • Jung K, Friede T and Beißbarth T (2011): Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genes. BMC Bioinformatics, 12:288. [open access, R-code]
  • Leha A, Beißbarth T and Jung K (2011): Sequential Interim Analyses of Survival Data in DNA Microarray Experiments. BMC Bioinformatics, 12:127. [open access]
  • Jung K, Becker B, Brunner E and Beißbarth T (2011): Comparison of global tests for functional gene sets in two-group designs and selection of potentially effect-causing genes. Bioin-formatics, 27, 1377-1383. [open access, R-package RepeatedHighDim]
  • Jung K, Grade M, Gaedtcke J, Jo P, Opitz L, Becker H, Ghadimi BM and Beißbarth T (2010): A new sensitivity-preferred strategy to build prediction rules for therapy response of cancer patients using gene expression data. Computer Methods and Programs in Biomedicine, 100, 132-139. [open access]
  • Jung K, Poschmann G, Podwojski K, Eisenacher M, Kohl M, Pfeiffer K, Meyer HE, Stühler K and Stephan C (2009): Adjusted Confidence Intervals for the Expression Change of Proteins observed in 2-Dimensional Difference Gel Electrophoresis. Journal of Proteomics & Bioinformatics, 2, 78-87. [open access, JAVA-Tool Statistical DIGE Analyzer]
  • Jung K, Quast K, Gannoun A and Urfer W (2006): A renewed approach to the nonparametric analysis of replicated microarray experiments. Biometrical Journal, 48, 245-254. [open access, R-package degenes]
  • Jung K, Gannoun A, Sitek B, Apostolov O, Schramm A, Meyer HE, Stühler K and Urfer W (2006): Statistical evaluation of methods for the analysis of dynamic protein expression data from a tumor study. RevStat-Statistical Journal, 4, 67-80. [pdf]
  • Jung K, Gannoun A, Stühler K, Sitek B, Meyer HE and Urfer W (2005): Analysis of dynamic protein expression data. RevStat-Statistical Journal, 3, 99-111. [pdf]

Awards and certificates

2020: Poster award for my PhD student Babak Saremi for the contribution "A bootstrap approach to estimate false positives in viral meta genomics" (B. Saremi, M. Kohls, K. Jung) presented at the IBS-DR/GMDS-Workshop on Computational Models in Biology and Medicine 2020 in Bonn, Germany.

2017: 1st price for the best teaching material in biometry (together with J. Kruppa; awarded by the working group teaching and didactics of biometry of the German Region of the International Biometric Sociecty)

2012: Certificate for Teaching in Higher Education (awarded by the University of Göttingen)

Memberships and activities in scientific societies

  • Memberships:
    • German Region of the International Biometric Society (IBS-DR)
    • German Society for Medical Informatics, Biometry and Epidemiology (GMDS)
    • International Society for Computational Biology (ISCB)
    • Fachgruppe Bioinformatik (FaBI)
  • 2016-2020: Secretary and board member of the IBS-DR
  • Speaker (2015-2018), since 2018 deputy speaker, of the working group "Statistical Methods in Bioinformatics" of the IBS-DR and the GMDS