Lukas Käll

发表

Response to "Comparison and Evaluation of Clustering Algorithms for Tandem Mass Spectra".

Johannes Griss, Yasset Perez-Riverol, Juan Antonio Vizcaíno, 2018, Journal of proteome research.

GradientOptimizer: An open‐source graphical environment for calculating optimized gradients in reversed‐phase liquid chromatography

Lukas Käll, Luminita Moruz, 2014, Proteomics.

A simple null model for inferences from network enrichment analysis

Lukas Käll, Gustavo S Jeuken, Gustavo S. Jeuken, 2018, PloS one.

An HMM posterior decoder for sequence feature prediction that includes homology information

Erik L. L. Sonnhammer, Anders Krogh, Lukas Käll, 2005, ISMB.

Non-parametric estimation of posterior error probabilities associated with peptides identified by tandem mass spectrometry

William Stafford Noble, Lukas Käll, John D. Storey, 2008, ECCB.

Engagera och aktivera studenter med inspiration från konferenser: examination genom posterpresentation

Lars Arvestad, Lukas Käll, Olof Emanuelsson, 2014 .

Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

William Stafford Noble, Barbara Frewen, Michael J. MacCoss, 2014, Journal of proteome research.

Expanding the Use of Spectral Libraries in Proteomics.

Johannes Griss, Yasset Perez-Riverol, Juan Antonio Vizcaíno, 2018, Journal of proteome research.

Solution to Statistical Challenges in Proteomics Is More Statistics, Not Less.

Lukas Käll, Oliver Serang, O. Serang, 2015, Journal of proteome research.

IPeak: An open source tool to combine results from multiple MS/MS search engines

Qiang Feng, Xun Xu, Andrew R Jones, 2015, Proteomics.

Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks

Jeff A. Bilmes, William Stafford Noble, Lukas Käll, 2008, PLoS Comput. Biol..

Proceedings of the 9th IAPR International Conference on Pattern Recognition in Bioinformatics - Volume 8626

Elena Marchiori, Alioune Ngom, Matteo Comin, 2014 .

Reliability of transmembrane predictions in whole‐genome data

Lukas Käll, Erik L L Sonnhammer, E. Sonnhammer, 2002, FEBS letters.

Predicting transmembrane topology and signal peptides with hidden Markov models

Lukas Käll, 2006 .

Computational Mass Spectrometry–Based Proteomics

Olga Vitek, Lukas Käll, L. Käll, 2011, PLoS Comput. Biol..

Uncertainty estimation of predictions of peptides' chromatographic retention times in shotgun proteomics

Matthew The, Lukas Käll, Heydar Maboudi Afkham, 2016, Bioinform..

Proceedings of the EuBIC-MS 2020 Developers’ Meeting

Wout Bittremieux, Yasset Perez-Riverol, Eric W. Deutsch, 2020, EuPA Open Proteomics.

The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides

Arne Elofsson, Nanjiang Shu, Lukas Käll, 2015, Nucleic Acids Res..

A protein standard that emulates homology for the characterization of protein inference algorithms

Samuel H Payne, Yasset Perez-Riverol, Magnus Palmblad, 2017, bioRxiv.

Transmembrane topology prediction

Erik L. L. Sonnhammer, Lukas Käll, E. Sonnhammer, 2004 .

MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

Matthew The, Lukas Käll, L. Käll, 2016, Journal of proteome research.

A cross-validation scheme for machine learning algorithms in shotgun proteomics

William Stafford Noble, Lukas Käll, Viktor Granholm, 2012, BMC Bioinformatics.

Advantages of combined transmembrane topology and signal peptide prediction—the Phobius web server

Erik L. L. Sonnhammer, Anders Krogh, Lukas Käll, 2007, Nucleic Acids Res..

Fast and accurate database searches with MS-GF+Percolator.

Erik Sjölund, Lukas Käll, Viktor Granholm, 2014, Journal of proteome research.

How to talk about protein‐level false discovery rates in shotgun proteomics

Matthew The, Lukas Käll, Ayesha Tasnim, 2016, Proteomics.

DeMix-Q: Quantification-Centered Data Processing Workflow*

Lukas Käll, Roman A Zubarev, Bo Zhang, 2016, Molecular & Cellular Proteomics.

qvality: non-parametric estimation of q-values and posterior error probabilities

William Stafford Noble, Lukas Käll, John D. Storey, 2009, Bioinform..

Speeding up Percolator.

William Stafford Noble, Ce Zhang, Kaan Kara, 2019, Journal of proteome research.

Integrated Identification and Quantification Error Probabilities for Shotgun Proteomics*

Matthew The, Lukas Käll, 2018, Molecular & Cellular Proteomics.

Improving the Comprehensiveness of Large-Scale Proteomics Experiments Using Advanced Computational Tools and Accurate Multiple Hypothesis Testing Statistics

William Stafford Noble, Barbara Frewen, Michael J. MacCoss, 2011 .

Performing Selection on a Monotonic Function in Lieu of Sorting Using Layer-Ordered Heaps.

Jake Pennington, Patrick Kreitzberg, Kyle Lucke, 2021, Journal of proteome research.

A general model of G protein‐coupled receptor sequences and its application to detect remote homologs

Lukas Käll, Markus Wistrand, Erik L L Sonnhammer, 2006, Protein science : a publication of the Protein Society.

Training, selection, and robust calibration of retention time models for targeted proteomics.

Lukas Käll, Luminita Moruz, L. Käll, 2010, Journal of proteome research.

Enhanced Peptide Identification by Electron Transfer Dissociation Using an Improved Mascot Percolator*

Markus Brosch, Lukas Käll, James C. Wright, 2012, Molecular & Cellular Proteomics.

Membrane topology of the Drosophila OR83b odorant receptor

Lukas Käll, Gunnar von Heijne, G. von Heijne, 2007, FEBS letters.

Mass fingerprinting of complex mixtures: protein inference from high-resolution peptide masses and predicted retention times.

Lukas Käll, Luminita Moruz, Magnus Rosenlund, 2013, Journal of proteome research.

Multi-omic data analysis using Galaxy

Pratik D Jagtap, Timothy J Griffin, Lukas Käll, 2015, Nature Biotechnology.

Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations.

Michael J MacCoss, William Stafford Noble, Lukas Käll, 2008, Genome research.

Peptide retention time prediction.

Lukas Käll, Luminita Moruz, L. Käll, 2017, Mass spectrometry reviews.

Recognizing uncertainty increases robustness and reproducibility of mass spectrometry-based protein inferences.

Lukas Käll, Luminita Moruz, Oliver Serang, 2012, Journal of proteome research.

On using samples of known protein content to assess the statistical calibration of scores assigned to peptide-spectrum matches in shotgun proteomics.

William Stafford Noble, Lukas Käll, Viktor Granholm, 2011, Journal of proteome research.

Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0

William Stafford Noble, Michael J. MacCoss, Matthew The, 2016, Journal of The American Society for Mass Spectrometry.

Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data*

Samuel H Payne, Michael J MacCoss, William Stafford Noble, 2015, Molecular & Cellular Proteomics.

The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides

Arne Elofsson, Nanjiang Shu, Lukas Käll, 2015 .

Optimized Nonlinear Gradients for Reversed-Phase Liquid Chromatography in Shotgun Proteomics

Karl Mechtler, Thomas Stranzl, Lukas Käll, 2013, Analytical chemistry.

Prediction of transmembrane topology and signal peptide given a protein's amino acid sequence.

Lukas Käll, L. Käll, 2010, Methods in molecular biology.