Fast and accurate database searches with MS-GF+ Percolator. V Granholm, S Kim, JCF Navarro, E Sjölund, RD Smith, L Käll. Journal of proteome research (2014), 13 (2), pp 890–897
Optimized nonlinear gradients for reversed-phase liquid chromatography in shotgun proteomics. L Moruz, P Pichler, T Stranzl, K Mechtler, L Käll. Analytical chemistry (2013) 85 (16), 7777-7785
Recognizing uncertainty increases robustness and reproducibility of mass spectrometry-based protein inferences O Serang, L Moruz, MR Hoopmann, L Käll. Journal of proteome research (2012), 11 (12), 5586-5591
On using samples of known protein content to assess the statistical calibration of scores assigned to peptide-spectrum matches in shotgun proteomics. V Granholm, WS Noble, L Käll. Journal of proteome research (2011), 10 (5), 2671-2678
Training, selection, and robust calibration of retention time models for targeted proteomics. L Moruz, D Tomazela, L Käll. Journal of proteome research( 2010) 9 (10), 5209-5216
Lukas Käll is Professor of Computational Proteomics at KTH Royal Institute of Technology, where his research focuses on developing machine learning methods to improve the analysis and interpretation of large-scale mass spectrometry–based proteomics data.
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