Lukas Käll
Lukas Käll
Professor, KTH Royal Institute of Technology, Science for Life Laboratory
Verified email at - Homepage
Cited by
Cited by
A combined transmembrane topology and signal peptide prediction method
L Käll, A Krogh, ELL Sonnhammer
Journal of molecular biology 338 (5), 1027-1036, 2004
Semi-supervised learning for peptide identification from shotgun proteomics datasets
L Käll, JD Canterbury, J Weston, WS Noble, MJ MacCoss
Nature methods 4 (11), 923-925, 2007
Advantages of combined transmembrane topology and signal peptide prediction—the Phobius web server
L Käll, A Krogh, ELL Sonnhammer
Nucleic acids research 35 (suppl_2), W429-W432, 2007
Assigning significance to peptides identified by tandem mass spectrometry using decoy databases
L Käll, JD Storey, MJ MacCoss, WS Noble
Journal of proteome research 7 (01), 29-34, 2008
The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides
KD Tsirigos, C Peters, N Shu, L Käll, A Elofsson
Nucleic acids research 43 (W1), W401-W407, 2015
An HMM posterior decoder for sequence feature prediction that includes homology information
L Käll, A Krogh, ELL Sonnhammer
Bioinformatics 21 (suppl_1), i251-i257, 2005
Posterior error probabilities and false discovery rates: two sides of the same coin
L Käll, JD Storey, MJ MacCoss, WS Noble
Journal of proteome research 7 (01), 40-44, 2008
Transmembrane topology and signal peptide prediction using dynamic bayesian networks
SM Reynolds, L Käll, ME Riffle, JA Bilmes, WS Noble
PLoS computational biology 4 (11), 2008
Membrane topology of the Drosophila OR83b odorant receptor
C Lundin, L Käll, SA Kreher, K Kapp, EL Sonnhammer, JR Carlson, ...
FEBS letters 581 (29), 5601-5604, 2007
Improvements to the percolator algorithm for Peptide identification from shotgun proteomics data sets
M Spivak, J Weston, L Bottou, L Käll, WS Noble
Journal of proteome research 8 (7), 3737-3745, 2009
Gene‐specific correlation of RNA and protein levels in human cells and tissues
F Edfors, F Danielsson, BM Hallström, L Käll, E Lundberg, F Pontén, ...
Molecular systems biology 12 (10), 2016
A general model of G protein‐coupled receptor sequences and its application to detect remote homologs
M Wistrand, L Käll, ELL Sonnhammer
Protein science 15 (3), 509-521, 2006
HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics
RMM Branca, LM Orre, HJ Johansson, V Granholm, M Huss, ...
Nature methods 11 (1), 59, 2014
qvality: non-parametric estimation of q-values and posterior error probabilities
L Käll, JD Storey, WS Noble
Bioinformatics 25 (7), 964-966, 2009
Rapid and accurate peptide identification from tandem mass spectra
CY Park, AA Klammer, L Käll, MJ MacCoss, WS Noble
Journal of proteome research 7 (7), 3022-3027, 2008
Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations
GE Merrihew, C Davis, B Ewing, G Williams, L Käll, BE Frewen, WS Noble, ...
Genome research 18 (10), 1660-1669, 2008
Reliability of transmembrane predictions in whole‐genome data
L Käll, ELL Sonnhammer
FEBS letters 532 (3), 415-418, 2002
Peptide-centric proteome analysis: an alternative strategy for the analysis of tandem mass spectrometry data
YS Ting, JD Egertson, SH Payne, S Kim, B MacLean, L Käll, R Aebersold, ...
Molecular & Cellular Proteomics 14 (9), 2301-2307, 2015
Crux: rapid open source protein tandem mass spectrometry analysis
S McIlwain, K Tamura, A Kertesz-Farkas, CE Grant, B Diament, B Frewen, ...
Journal of proteome research 13 (10), 4488-4491, 2014
Multi-omic data analysis using Galaxy
J Boekel, JM Chilton, IR Cooke, PL Horvatovich, PD Jagtap, L Käll, ...
Nature biotechnology 33 (2), 137-139, 2015
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