Select Page
Alternativer Text



An up-to-date list of publications of Prof. Dr. Dominik Grimm can be found on Google Scholar or on ResearchGate.

Book Chapters, Workshop Proceedings, Abstracts and Patents can be found after the peer reviewed articles.



  • Self-Improvement for Neural Combinatorial Optimization: Sample Without Replacement, but Improvement
    J Pirnay, DG Grimm
    Transactions on Machine Learning Research (TMLR), 2024 ( [Code] {Awarded with “Featured” Certification}
  • Forecasting Seasonally Fluctuating Sales of Perishable Products in the Horticultural Industry
    J Eiglsperger, F Haselbeck, V Stiele, C Guadarrama Serrano, K Lim-Trinh, K Menrad, T Hannus, DG Grimm
    Expert Systems with Applications, 2024 (
  • Superior Protein Thermophilicity Prediction With Protein Language Model Embeddings
    F Haselbeck, M John, Y Zhang, J Pirnay, JP Fuenzalida-Werner, RD Costa, DG Grimm
    NAR Genomics and Bioinformatics, 2023 ( [Code]
  • Combining Machine Learning and Optimization for the Operational Patient-Bed Assignment Problem
    F Schäfer, M Walther, DG Grimm, A Hübner
    Health Care Management Science, 2023 (
  • Improved Weed Segmentation in UAV Imagery of Sorghum Fields with a Combined Deblurring Segmentation Model 
    N Genze, M Wirth, C Schreiner, Raymond Ajewkwe, M Grieb, DG Grimm
    Plant Methods, 2023 ( [Code, Data]
  • Systematic analysis of the underlying genomic architecture for transcriptional-translational coupling in prokaryotes.
    R Bharti, D Siebert, B Blombach*, DG Grimm*
    NAR Genomics and Bioinformatics, 2022 ( [Code]
  • Rat Hepatic Stellate Cell Line CFSC-2G: Genetic Markers and Short Tandem Repeat Profile Useful for Cell Line Authentication.
    I Nanda, SK Schröder, C Steinlein, T Haaf, EM Buhl, DG Grimm, R Weiskirchen
    Cells, 2022 (
  • Deep Learning-based Early Weed Segmentation using Motion Blurred UAV Images of Sorghum Fields.
    N Genze, R Ajekwe, Z Güreli, F Haselbeck, M Grieb, DG Grimm
    Computers and Electronics in Agriculture, 2022 ( [Code, Data]
  • A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species.
    M John*, F Haselbeck*, R Dass, C Malisi, P Ricca, C Dreischer, SJ Schultheiss, DG Grimm
    Frontiers in Plant Science, 2022 ( [Code]
  • Using Reinforcement Learning in a Game-like Setup for Automated Process Synthesis without Prior Process Knowledge.
    Q Göttl, DG Grimm, J Burger
    Proceedings of the 14th International Symposium on Process Systems Engineering, 2022 ( [Code]
  • Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward.
    S Omranian, Z Nikoloski, DG Grimm
    Computational and Structural Biotechnology Journal, 2022 (
  • Genetic Characterization of Rat Hepatic Stellate Cell Line HSC-T6 for In Vitro Cell Line Authentication.
    I Nanda, C Steinlein, T Haaf, EM Buhl, DG Grimm, SL Friedman, SK Murer, SK Schröder, R Weiskirchen
    Cells, 2022 (
  • Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions  
    F Haselbeck, J Killinger, K Menrad, T Hannus, DG Grimm
    Machine Learning with Applications, 2022 ( [Code]
* Equal contributions
  • The AIMe registry for artificial intelligence in biomedical research
    J Matschinske, N Alcaraz, A Benis, M Golebiewski, DG Grimm, L Heumos, T Kacprowski, O Lazareva, M List, Z Louadi, JK Pauling, N Pfeifer, R Röttger, V Schwämmle, G Sturm, A Traverso, K Van Steen, M Vaz de Freitas, G Villalba Silva, L Wee, N Wenke, M Zanin, O Zolotareva, J Baumbach, DB Blumenthal
    Nature Methods, 2021 ( [AIMe Web Service:; Code: Backend, Frontend]
  • Automated Flowsheet Synthesis Using Hierarchical Reinforcement Learning: proof of concept.
    Q Göttl, YH Tönges, DG Grimm, J Burger
    Chemie Ingenieur Technik, 2021 ( [Code]
  • AraPheno and the AraGWAS Catalog 2020: A major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana.
    M Togninalli*, Ü Seren*, JA Freudenthal, JG Monroe, D Meng, M Nordborg, D Weigel, KM Borgwardt, A Korte, DG Grimm
    Nucleic Acids Research (NAR), 48 (D1), D1063-D1068 ( [Code] * Shared first authorship
  • Exosome-based detection of activating and resistance EGFR mutations from plasma of non-small cell lung cancer patients.
    E Castellanos-Rizaldos, X Zhang, VR Tadigotla, DG Grimm, C Karlovich, LE Raez, JK Skog
    Oncotarget, 2019, 10(30): 2911-2920 (PubMed: Link)
  • Linking Genomic and Metabolomic Natural Variation Uncovers Nematode Pheromone Biosynthesis.
    JM Falcke, N Bose, AB Artyukhin, C Rödelsperger, GV Markov  JJ Yim, DG Grimm, MH Claassen, O Panda, JA Baccile, YK Zhang, HH Le, D Jolic, FC Schroeder, RJ Sommer
    Cell Chemical Biology, 25.6 (2018): 787-796. (Link)
  • Exosome-based Detection of EGFR T790M in Plasma from Non-Small Cell Lung Cancer Patients.
    E Castellanos-Rizaldos, DG Grimm, V Tadigotla, J Hurley, J Healy, PL Neal, M Sher, R Venkatesan, C Karlovich, M Raponi, AK Krug, M Noerholm, J Tannous, BA Tannous, LE Real, J Skog
    Clinical Cancer Research (CCR), 24.12 (2018): 2944-2950 (Link)

  • The AraGWAS Catalog: A curated and standardized Arabidopsis thaliana GWAS catalog.
    M Togninalli*, Ü Seren*, M Dazhe, F Joffrey, M Nordborg, D Weigel, KM Borgwardt, A Korte and DG Grimm
    Nucleic Acids Research (NAR), 46.D1 (2018): D1150-D1156 (Link)
  • The rate and potential relevance of new mutations in a colonizing plant lineage.
    M Exposito-Alonso*, C Becker*, VJ Schuenemann, E Reitter, C Setzer, R Slovak, B Brachi, J Hagmann, DG Grimm, C Jiahui, W Busch, J Bergelson, RW Ness, J Krause, HA Burbano and D Weigel
    PLoS Genetics, 14.2 (2018): e1007155 (Link)
  • Improved EGFR mutation detection using combined exosomal RNA and circulating tumor DNA in NSCLC patient plasma.
    AK Krug,* D Enderle*, C Karlovich, T Priewasser, S Bentik, A Spiel, K Brinkmann, J Emenegger, DG Grimm, E Castellanos-Rizaldos, JW Goldman, LV Sequist, JC Soria, DR Camidge, SM Gadgeel, HA Wakelee, M Raponi, M Noerholm, J Skog
    Annals of Oncology, 29.3 (2017): 700-706. (Link)
  • easyGWAS: A cloud-based platform for comparing the results of genome-wide association studies.
    DG Grimm, D Roqueiro, PA Salome, S Kleeberger, B Greshake, W Zhu, C Liu, C Lippert, O Stegle, B Schölkopf, D Weigel and KM Borgwardt
    The Plant Cell, 2017, 29 (1): 5-19 (Link)
  • AraPheno: A public database for Arabidopsis thaliana phenotypes.
    Ü Seren*, DG Grimm*, J Fitz, D Weigel, M Nordborg, KM Borgwardt, A Korte
    Nucleic Acids Research (NAR), 2017, 45(D1), D1054-D1059
    * Shared first authorship (Link)
  • The Genetic Architecture of Non-additive Inheritance in Arabidopsis thaliana Hybrids.
    DK Seymour*, E Chae*, DG Grimm*, CM Pizzaro, A Haeing-Müller, F Vasseur, B Rakitsch, KM Borgwardt, D Koenig and D Weigel
    Proceedings of the National Academy of Sciences (PNAS), 2016, 113 (46), E7317-E7326
    * Shared first authorship (Link)
  • Epigenomic Diversity in a Global Collection of Arabidopsis thaliana Accessions.
    Taiji Kawakatsu, Shao-shan Carol Huang, Florian Jupe, Eriko Sasaki, Robert J. Schmitz, Mark A. Urich, Rosa Castanon, Joseph R. Nery, Cesar Barragan, Yupeng He, Huaming Chen, Manu Dubin, Cheng-Ruei Lee, Congmao Wang, Felix Bemm, Claude Becker, Ryan O’Neil, Ronan C. O Malley, Danjuma X. Quarless, The 1001 Genomes Consortium*, Nicholas J. Schork, Detlef Weigel, Magnus Nordborg, Joseph R.
    Cell 166.2 (2016): 492-505
    * As part of the 1001 Genomes Consortium (Link)
  • Genomic profiles of diversification and genotype-phenotype association in island nematode lineages.
    A McGaughran, C Rödelsperger, DG Grimm, JM Meyer, E Moreno, K Morgan, M Leaver, V Serobyan, B Rakitsch, KM Borgwardt, RJ Sommer
    Molecular Biology and Evolution (2016) 33 (9): 2257-2272. (Link)
  • 1135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana.
    The 1001 Genomes Consortium*
    Cell 166.2 (2016): 481-491
    * As part of the 1001 Genomes Consortium (Link)
  • The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity.
    DG Grimm, CA Azencott, F Aicheler, U Gieraths, DG MacArthur, KE Samocha, DN Cooper, PD Stenson, MJ Daly, JW Smoller, LE Duncan and KM Borgwardt
    Human Mutation 2015, 36(5):513-523 (Link)
  • Genome-wide detection of intervals of genetic heterogeneity associated with complex traits.
    F Llinares-López, DG Grimm, DA Bodenham, U Gieraths, M Sugiyama, B Rowan, KM Borgwardt
    Bioinformatics (2015) 31(12):i303-i310 (Link)
  • Prediction of human population responses to toxic compounds by a collaborative competition.
    Eduati F, Mangravite ML, Wang T, Tang H, Bare JC, Huang R, Norman T, Kellen M, Menden PM, Yang J, Zhan X, Zhong R, Xiao G, Xia M, Abdo N, Kosyk O, NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration*, Friend S, Dearry A, Simeonov A, Tice RR, Rusyn I, Wright FA, Stolovitzky G, Xie Y, Saez-Rodriguez J
    Nature Biotechnology 2015 (Link)
    * As part of the NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration
  • Genome-wide analysis of local chromatin packing in Arabidopsis thaliana.
    C Wang, C Liu, D Roqueiro, DG Grimm, R Schwab, C Becker, C Lanz, D Weigel
    Genome Research, 2015. 25: 246-256 (Link)
  • Multi-task feature selection with multiple networks via maximum flows.
    M Sugiyama, CA Azencott, DG Grimm, Y Kawahara and K Borgwardt
    SIAM International Conference on Data Mining (SDM 2014) (Link)
  • Efficient network-guided multi-locus association mapping with graph cuts.
    CA Azencott, DG Grimm, M Sugiyama, Y Kawahara and K Borgwardt
    Bioinformatics 2013, 29(13):i171-i179 (Link)
  • Accurate indel prediction using paired-end short reads.
    DG Grimm*, J Hagmann*, D Koenig, D Weigel and K Borgwardt
    BMC Genomics 2013, 14:132 (Link)
    * Shared first authorship
  • Geometric tree kernels: Classification of COPD from airway tree geometry.
    A Feragen, J Petersen, DG Grimm, A Dirksen, JH Pedersen, K Borgwardt, M de Bruijne
    Information Processing in Medical Imaging (IPMI 2013), Lecture Notes in Computer Science Volume 7917, 171-183 (Link)
  • Computational inference of difficult word boundaries in DNA languages.
    G Tsafnat, P Setzermann, DG Grimm and S Partridge
    Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2011), ACM, New York, USA, 5 pages. (Link)


Books and Book Chapters

Maura JohnDominik Grimm, Arthur Korte (2023)
Predicting Gene Regulatory Interactions Using Natural Genetic Variation
In: Kaufmann, K., Vandepoele, K. (eds) Plant Gene Regulatory Networks.
Methods in Molecular Biology, vol 2698. Humana, New York, NY (Link)


Richa Bharti, Dominik G Grimm (2021)
Design and Analysis of RNA Sequencing Data
In: Melanie Kappelmann-Fenzl. Next Generation Sequencing and Data Analysis.
Learning Materials in Biosciences. Springer, Cham. (Link)


Anja C Gumpinger, Damian Roqueiro, Dominik G Grimm, Karsten M Borgwardt (2018)
Methods and Tools in Genome-Wide Association Studies
In: von Stechow L., Santos Delgado A. (eds) Computational Cell Biology. Methods in Molecular Biology, vol 1819. Humana Press, New York, NY (Link)

Abstracts, Workshop Proceedings & Posters

  • Automatisierte Fließbildsynthese durch Reinforcement Learning
    Q Göttl, DG Grimm, J Burger
    10. ProcessNet‐Jahrestagung und 34. DECHEMA‐Jahrestagung der Biotechnologen 2020: Processes for Future, 2020
  • MiCroM: A Comprehensive Pipeline for Gene Amplicon and Metagenomic Data Analysis
    Bharti R.Grimm, D. G.
    German Conference on Bioinformatics (GCB), 2019
  • MiCroM: A Comprehensive Pipeline for Gene Amplicon and Metagenomic Data Analysis
    Bharti R.Grimm, D. G.
    27th Conference on Intelligent Systems for Molecular Biology (ISMB), 2019
  • Hybrid heuristic for the patient-bed allocation problem.
    Schäfer F., Hübner A., Grimm, D. G.
    European Conference on Operational Research (EURO), 2019 (Link)
  • Exosome-based detection of EGFR T790M in plasma from non-small cell lung cancer patients.
    Castellanos-Rizaldos, E., Grimm, D. G., Tadigotla, V., Hurley, J., Healy, J., Neal, P. L., … & Krug, A. K..
    Clinical Cancer Research, 2018 (Link)
  • easyGWAS: A cloud-based platform for comparing the results of genome-wide association studies
    Dominik G. Grimm, Damian Roqueiro, Matteo Togninalli, easyGWAS Consortium and Karsten Borgwardt
    Intelligent Systems for Molecular Biology (ISMB), Technology Track Presentation, 2017 (Link, Abstract)
  • Long RNA sequencing of human plasma exosomes reveals full coverage of diverse protein coding and long non coding RNA.
    Chakrabortty, S. K., Bedford, L., Uchiyama, H., Tadigotla, V., Valentino, M. D., Grimm, D., … & Skog, J. 
    Cancer Research, 2017 (Link)
  • Plasma EGFR T790M mutation detection in NSCLC patients using a combined exosomal RNA and circulating tumor DNA qPCR assay.
    Castellanos-Rizaldos, E., Grimm, D. G., Tadigotla, V., Bentink, S., Hurley, J., Healy, J., … & Karlovich, C.
    European Journal of Cancer, 69, S3., 2016 (Link)
  • easyGWAS: A central resource for efficient performance of genome-wide association studies
    Dominik Grimm, Bastian Greshake, Oliver Stegle, Christoph Lippert, Bernhard Schölkopf, Detlef Weigel, Karsten Borgwardt
    International PhD Program in the Biological Sciences, Max Planck Institute for Developmental Biology, Germany (2012).
  • Support Vector Machines for Finding Deletions and Short Insertions Using Paired-End Short Reads.
    Grimm, D. G., Hagmann, J., Koenig, D., Weigel, D., & Borgwardt, K.
    Machine Learning Sommer School, MLSS, 2011 (Link)
  • Support Vector Machines for finding deletions and short insertions using paired-end short reads.
    Grimm, D. G., Hagmann, J., Koenig, D., Weigel, D., & Borgwardt, K.
    Intelligent Systems for Molecular Biology (ISMB), 2011 (Link)


  • Johan Skog, Elena Castellanos-Rizaldos, Vasisht Tadigotla, Dominik Grimm, Xuan Zhang, Wei Yu (2018)
    Methods and compositions to detect mutations in plasma using exosomal rna and cell free dna from non-small cell lung cancer patients. 


  • Johan Skog, Sudipto Chakrabortty, Dalin Chan, Michael Valentino, Vasisht Tadigotla, Robert Kitchen, Dominik Grimm, Wei Yu (2018)
    Sequencing and analysis of exosome associated nucleic acids. 


Professorship Bioinformatics

Petersgasse 18
94315 Straubing


Prof. Dr. Dominik Grimm

Phone: +49 (0) 9421 187-230


Team Assistants

Anna Fischer

Phone: +49 (0) 9421 187-231

Jasmin Schneider

Phone: +49 (0) 9421 187-201