Oliver Kohlbacher

This paper introduces a workflow that decouples quantification and identification in label-free top-down proteomics, improving proteome coverage and quantification precision.

This paper introduces Immunotype, a deep learning model that directly types HLA alleles from immunopeptidomics data with 87.2% accuracy.

pmultiqc generates metadata-aware QC reports for proteomics data using standardized metrics and integrates with existing workflows and cloud services.

quantms-rescoring improves proteomics analysis by integrating multiple search engines and machine learning, increasing identified spectra and quantifying more phosphorylated peptides and modification sites.

The paper introduces chemical crosslinking with mass spectrometry and a new search engine, NuXL, to identify nucleic acid-protein crosslinks at amino acid resolution, enhancing structural analysis.

FLASHQuant is a fast, accurate, and open-source algorithm for label-free quantification of proteoforms in top-down proteomics, resolving co-eluting signals efficiently.

This study analyzes genome and transcriptome data from discordant monozygotic twins with Mayer-Rokitansky-Kuster-Hauser syndrome to identify genetic and transcriptional differences.

MassQL, an open-source query language, lets users search raw mass spectrometry data from any vendor for isotope, fragmentation and neutral-loss patterns, from one file to entire public repositories.

DeRegNet identifies maximally deregulated subnetworks from multi-omics data using a novel algorithm, outperforming existing methods and identifying biologically relevant subgraphs in liver cancer.

FLASHIda improves proteoform identification in top-down proteomics by intelligently selecting precursors, doubling identification counts in E. coli lysates.

The paper introduces a standardized metadata format for proteomics datasets to improve reusability and integration across public repositories.

PeCaX is a visual analytics tool that helps molecular tumor boards interpret somatic genomic variants by integrating clinical annotations and gene-drug networks into interactive visualizations.

DIAproteomics is an automated pipeline for analyzing DIA proteomics and peptidomics data, offering tools for spectral library generation, alignment, and statistical analysis.

SmartPeak automates metabolomics data processing with algorithms for alignment, calibration, and peak integration, improving reproducibility and throughput.

This study profiles endometrial tissue from MRKH syndrome patients using RNA-seq to identify altered transcription patterns and candidate genes involved in the syndrome.

The paper introduces FBMN, a method for improving molecular networking by enhancing quantitative analysis and isomer distinction using feature detection and alignment tools in the GNPS platform.

The paper presents the HLA Ligand Atlas, a resource of HLA-I and -II ligands from benign tissues, showing tissue and individual differences and non-canonical ligand origins.

The paper introduces NASE, a database search engine for RNA mass spectrometry data, demonstrating its ability to identify modified RNA sequences in three datasets.

FLASHDeconv improves feature deconvolution in top-down proteomics by accelerating the process and enhancing quality.

EPIFANY improves protein inference accuracy and efficiency by combining loopy belief propagation with convolution trees, outperforming existing methods on benchmark data.

The paper uses sequence coevolution to predict protein interactions in E. coli, identifying 620 new interactions and their structures.

The paper analyzes genetic variation in 806 drug-related genes using 60,706 human exomes, finding that most variants are rare but many patients carry functional variants affecting drug efficacy and risk varies by ancestry.