Kohlbacher, Oliver

Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment

Schulte-Schrepping, J., Reusch, N., Paclik, D., Baßler, K., Schlickeiser, S., Zhang, B., Krämer, B., Krammer, T., Brumhard, S., Bonaguro, L., et al. (2020) · Cell

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 Research

Cited by 1,461

Charting a dynamic DNA methylation landscape of the human genome

Ziller, M. J., Gu, H., Müller, F., Donaghey, J., Tsai, L. T.-Y., Kohlbacher, O., De Jager, P. L., Rosen, E. D., Bennett, D. A., Bernstein, B. E., et al. (2013) · Nature

Epigenetics and DNA MethylationGenomics and Chromatin Dynamics

Cited by 1,357

Swarm Learning for decentralized and confidential clinical machine learning

Warnat-Herresthal, S., Schultze, H., Shastry, K. L., Manamohan, S., Mukherjee, S., Garg, V., Sarveswara, R., Händler, K., Pickkers, P., Aziz, N. A., et al. (2021) · Nature

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 884

SARS-CoV-2-derived peptides define heterologous and COVID-19-induced T cell recognition

Nelde, A., Bilich, T., Heitmann, J. S., Maringer, Y., Salih, H. R., Roerden, M., Lübke, M., Bauer, J., Rieth, J., Wacker, M., et al. (2021) · Nature Immunology

vaccines and immunoinformatics approachesSARS-CoV-2 and COVID-19 Research

Cited by 582

Sequence co-evolution gives 3D contacts and structures of protein complexes

Hopf, T. A., Schärfe, C. P. I., Rodrigues, J. P. G. L. M., Green, A. G., Kohlbacher, O., Sander, C., Bonvin, A. M. J. J., & Marks, D. S. (2014) · eLife

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 515

Transcriptional and Epigenetic Dynamics during Specification of Human Embryonic Stem Cells

Gifford, C. A., Ziller, M. J., Gu, H., Trapnell, C., Donaghey, J., Tsankov, A., Shalek, A. K., Kelley, D. R., Shishkin, A. A., Issner, R., et al. (2013) · Cell

Pluripotent Stem Cells ResearchEpigenetics and DNA Methylation

Cited by 435

HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy

Marcu, A., Bichmann, L., Kuchenbecker, L., Kowalewski, D. J., Freudenmann, L. K., Backert, L., Mühlenbruch, L., Szolek, A., Lübke, M., Wagner, P., et al. (2021) · Journal for ImmunoTherapy of Cancer

vaccines and immunoinformatics approachesImmunotherapy and Immune Responses

Cited by 250

An automated pipeline for high-throughput label-free quantitative proteomics

Weisser, H., Nahnsen, S., Grossmann, J., Nilse, L., Quandt, A., Brauer, H., Sturm, M., Kenar, E., Kohlbacher, O., Aebersold, R., et al. (2013) · Journal of Proteome Research

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 160

Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences

Green, A. G., Elhabashy, H., Brock, K. P., Maddamsetti, R., Kohlbacher, O., & Marks, D. S. (2021) · Nature Communications

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 114

FLASHDeconv: Ultrafast, High-Quality Feature Deconvolution for Top-Down Proteomics

Jeong, K., Kim, J., Gaikwad, M., Hidayah, S. N., Heikaus, L., Schlüter, H., & Kohlbacher, O. (2020) · Cell Systems

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 82

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort

Magunia, H., Lederer, S., Verbuecheln, R., Gilot, B. J., Koeppen, M., Haeberle, H. A., Mirakaj, V., Hofmann, P., Marx, G., Bickenbach, J., et al. (2021) · Critical Care

COVID-19 Clinical Research StudiesMachine Learning in Healthcare

Cited by 65

Chemical crosslinking extends and complements UV crosslinking in analysis of RNA/DNA nucleic acid–protein interaction sites by mass spectrometry

Welp, L. M., Wulf, A., Chernev, A., Horokhovskyi, Y., Moshkovskii, S., Dybkov, O., Neumann, P., Pašen, M., Siraj, A., Raabe, M., et al. (2025) · Nucleic Acids Research

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 12

Perspectives in computational mass spectrometry: recent developments and key challenges

Sachsenberg, T., Pino, L. K., Brunet, M., Bludau, I., Kohlbacher, O., Vizcaino, J. A., & Bittremieux, W. (2024) · Bioinformatics Advances

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 6