Lukas Käll

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William Stafford NobleProfessor of Genome Sciences, University of WashingtonVerified email at uw.edu
Erik SonnhammerProfessor of Bioinformatics, DBB Stockholm University, Science for Life LaboratoryVerified email at scilifelab.se
Michael MacCossProfessor of Genome Sciences, University of WashingtonVerified email at uw.edu
Anders KroghDepartment of Computer Science and Center for Health Data Science, University of CopenhagenVerified email at di.ku.dk
Viktor GranholmStockholm UniversityVerified email at scilifelab.se
John D. StoreyProfessor, Princeton UniversityVerified email at princeton.edu
Matthew TheTU MunichVerified email at tum.de
Jason WestonFacebookVerified email at fb.com
Arne ElofssonScience for Life Laboratory and department of Biochemistry and Biophysics, Stockholm UniversityVerified email at bioinfo.se
Michael R. HoopmannInstitute for Systems BiologyVerified email at systemsbiology.org
Fredrik EdforsThe Royal Institute of Technology (KTH)Verified email at scilifelab.se
Konstantinos Tsirigos, PhD Bioinforma...European Bioinformatics instituteVerified email at ebi.ac.uk
Mathias UhlénScience for Life Laboratory, KTH, StockholmVerified email at scilifelab.se
Janne LehtiöKarolinska Institutet, SciLifeLabVerified email at scilifelab.se
Jeffrey A. BilmesProfessor of Electrical Engineering and Computer Science, University of Washington SeattleVerified email at uw.edu
Michael RiffleUniversity of WashingtonVerified email at uw.edu
Samuel H PayneAssociate Professor, Brigham Young UniversityVerified email at byu.edu
Nanjiang ShuDepartment of Biochemistry and Biophysics, Stockholm UniversityVerified email at scilifelab.se
Sangtae KimSeerVerified email at seer.bio
Richard D SmithChief Scientist and Battelle Fellow, Biological Sciences Division, PNNLVerified email at pnnl.gov

Lukas Käll

Professor, KTH Royal Institute of Technology, Science for Life Laboratory

Verified email at kth.se - Homepage

Computational Biology Proteomics Machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A combined transmembrane topology and signal peptide prediction method L Käll, A Krogh, ELL Sonnhammer Journal of molecular biology 338 (5), 1027-1036, 2004	2134	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	1585	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	1244	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	631	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	538	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	319	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	295	2008
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), 883, 2016	288	2016
Improvements to the percolator algorithm for peptide identification from shotgun proteomics data sets M Spivak, J Weston, L Bottou, L Kall, WS Noble Journal of proteome research 8 (7), 3737-3745, 2009	247	2009
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), e1000213, 2008	240	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	221	2007
HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics RMM Branca, LM Orre, HJ Johansson, V Granholm, M Huss, ... Nature methods 11 (1), 59-62, 2014	208	2014
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	195	2006
Rapid and accurate peptide identification from tandem mass spectra CY Park, AA Klammer, L Kall, MJ MacCoss, WS Noble Journal of proteome research 7 (7), 3022-3027, 2008	188	2008
Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry L Käll, JD Storey, WS Noble Bioinformatics 24 (16), i42-i48, 2008	127	2008
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	119	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	106	2014
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	102	2008
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	101	2015
Fast and accurate protein false discovery rates on large-scale proteomics data sets with Percolator 3.0 M The, MJ MacCoss, WS Noble, L Käll J. Am. Soc. Mass Spectrom 27 (11), 1719, 2016	99	2016

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