Manfred Claassen
Manfred Claassen
University of Tübingen / University Hospital of Tübingen
Verified email at
Cited by
Cited by
The quantitative proteome of a human cell line
M Beck, A Schmidt, J Malmstroem, M Claassen, A Ori, A Szymborska, ...
Molecular systems biology 7 (1), 549, 2011
Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry
L Reiter, M Claassen, SP Schrimpf, M Jovanovic, A Schmidt, JM Buhmann, ...
Molecular & Cellular Proteomics 8 (11), 2405-2417, 2009
False discovery rate estimation for cross-linked peptides identified by mass spectrometry
T Walzthoeni, M Claassen, A Leitner, F Herzog, S Bohn, F Förster, M Beck, ...
Nature methods 9 (9), 901-903, 2012
Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability
P Leuenberger, S Ganscha, A Kahraman, V Cappelletti, PJ Boersema, ...
Science 355 (6327), 2017
Automated Gleason grading of prostate cancer tissue microarrays via deep learning
E Arvaniti, KS Fricker, M Moret, N Rupp, T Hermanns, C Fankhauser, ...
Scientific reports 8 (1), 1-11, 2018
The Mtb proteome library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis
OT Schubert, J Mouritsen, C Ludwig, HL Röst, G Rosenberger, PK Arthur, ...
Cell host & microbe 13 (5), 602-612, 2013
Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry
C Ludwig, M Claassen, A Schmidt, R Aebersold
Molecular & Cellular Proteomics 11 (3), 2012
Directed mass spectrometry: towards hypothesis-driven proteomics
A Schmidt, M Claassen, R Aebersold
Current opinion in chemical biology 13 (5-6), 510-517, 2009
Absolute quantification of microbial proteomes at different states by directed mass spectrometry
A Schmidt, M Beck, J Malmström, H Lam, M Claassen, D Campbell, ...
Molecular systems biology 7 (1), 510, 2011
Comprehensive proteomics
M Beck, M Claassen, R Aebersold
Current opinion in biotechnology 22 (1), 3-8, 2011
Nontargeted metabolomics reveals the multilevel response to antibiotic perturbations
M Zampieri, M Zimmermann, M Claassen, U Sauer
Cell reports 19 (6), 1214-1228, 2017
Sensitive detection of rare disease-associated cell subsets via representation learning
E Arvaniti, M Claassen
Nature communications 8 (1), 1-10, 2017
GM-CSF and CXCR4 define a T helper cell signature in multiple sclerosis
E Galli, FJ Hartmann, B Schreiner, F Ingelfinger, E Arvaniti, M Diebold, ...
Nature medicine 25 (8), 1290-1300, 2019
NASH limits anti-tumour surveillance in immunotherapy-treated HCC
D Pfister, NG Núñez, R Pinyol, O Govaere, M Pinter, M Szydlowska, ...
Nature 592 (7854), 450-456, 2021
Inference and validation of protein identifications
M Claassen
Molecular & cellular proteomics 11 (11), 1097-1104, 2012
The dynamics of root cap sloughing in Arabidopsis is regulated by peptide signalling
CL Shi, D Von Wangenheim, U Herrmann, M Wildhagen, I Kulik, A Kopf, ...
Nature plants 4 (8), 596-604, 2018
The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases
SIB Swiss Institute of Bioinformatics Members
Nucleic acids research 44 (D1), D27-D37, 2016
TGF-β induces oncofetal fibronectin that, in turn, modulates TGF-β superfamily signaling in endothelial cells
E Ventura, M Weller, W Macnair, K Eschbach, C Beisel, C Cordazzo, ...
Journal of cell science 131 (1), jcs209619, 2018
Similarities and differences of blood N-glycoproteins in five solid carcinomas at localized clinical stage analyzed by sWATH-MS
T Sajic, Y Liu, E Arvaniti, S Surinova, EG Williams, R Schiess, ...
Cell reports 23 (9), 2819-2831. e5, 2018
Analysis of cell lineage trees by exact Bayesian inference identifies negative autoregulation of Nanog in mouse embryonic stem cells
J Feigelman, S Ganscha, S Hastreiter, M Schwarzfischer, A Filipczyk, ...
Cell systems 3 (5), 480-490. e13, 2016
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