Claassen, Manfred

NASH limits anti-tumour surveillance in immunotherapy-treated HCC

Pfister, D., Núñez, N. G., Pinyol, R., Govaere, O., Pinter, M., Szydlowska, M., Gupta, R., Qiu, M., Deczkowska, A., Weiner, A., et al. (2021) · Nature

Cancer Immunotherapy and BiomarkersHepatocellular Carcinoma Treatment and Prognosis

Cited by 1,294

The quantitative proteome of a human cell line

Beck, M., Schmidt, A., Malmstroem, J., Claassen, M., Ori, A., Szymborska, A., Herzog, F., Rinner, O., Ellenberg, J., & Aebersold, R. (2011) · Molecular Systems Biology

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 816

Protein Identification False Discovery Rates for Very Large Proteomics Data Sets Generated by Tandem Mass Spectrometry

Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 312

Intestinal B cells license metabolic T-cell activation in NASH microbiota/antigen-independently and contribute to fibrosis by IgA-FcR signalling

Kotsiliti, E., Leone, V., Schuehle, S., Govaere, O., Li, H., Wolf, M. J., Horvatic, H., Bierwirth, S., Hundertmark, J., Inverso, D., et al. (2023) · Journal of Hepatology

Liver Disease Diagnosis and TreatmentLiver physiology and pathology

Cited by 108

Comprehensive proteomics

Beck, M., Claassen, M., & Aebersold, R. (2011) · Current Opinion in Biotechnology

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 83

Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition

Bues, J., Biočanin, M., Pezoldt, J., Dainese, R., Chrisnandy, A., Rezakhani, S., Saelens, W., Gardeux, V., Gupta, R., Sarkis, R., et al. (2022) · Nature Methods

Single-cell and spatial transcriptomicsInnovative Microfluidic and Catalytic Techniques Innovation

Cited by 71

Assessing AI awareness and identifying essential competencies: insights from key stakeholders in integrating AI into medical education

Moldt, J.-A., Festl-Wietek, T., Fuhl, W., Zabel, S., Claassen, M., Wagner, S., Nieselt, K., & Herrmann-Werner, A. (2024) · JMIR Medical Education

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 47

Multiomics analysis of immune correlatives in hepatocellular carcinoma patients treated with tremelimumab plus durvalumab

Myojin, Y., Babaei, S., Trehan, R., Hoffman, C., Kedei, N., Ruf, B., Benmebarek, M.-R., Bauer, K. C., Huang, P., Ma, C., et al. (2025) · Gut

Cancer Immunotherapy and BiomarkersHepatocellular Carcinoma Treatment and Prognosis

Cited by 24

Metabolic network segmentation: a probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data

Kuehne, A., Mayr, U., Sévin, D. C., Claassen, M., & Zamboni, N. (2017) · PLoS Computational Biology

Microbial Metabolic Engineering and BioproductionBioinformatics and Genomic Networks

Cited by 9

Proteome Coverage Prediction for Integrated Proteomics Datasets

Claassen, M., Aebersold, R., & Buhmann, J. M. (2011) · Journal of Computational Biology

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 8