Hannes Luc Röst

HiMaLAYAS, a Python package, cuts dendrograms, tests clusters for categorical annotation enrichment (hypergeometric, Benjamini-Hochberg FDR), and renders significant annotations beside clustered heatmaps in one workflow.

OpenLipid uses a large language model to analyze DIA mass spectrometry data for lipid identification, achieving high accuracy compared to existing methods.

STRIDE improves phosphopeptide quantification by reducing false negatives and enhancing consistent peak assignment across DIA-MS runs.

The paper improves library construction for low-input proteomics by using reference samples, showing significant performance gains in both OpenSWATH and DIA-NN workflows.

This paper benchmarks prior bias in deep learning models for de novo peptide sequencing using a novel framework called DeNovo-PBI.

This study maps spatiotemporal changes in cytoskeletal and junctional protein interactions during somatic cell reprogramming using time-resolved proximity proteomics.

ChatDIA uses a zero-shot large language model to automate targeted DIA proteomics analysis with high accuracy and transparent rationales.

The paper expands TheCellMap.org to include human genetic interactions from CRISPR-based analysis in HAP1 cells, enabling visualization and exploration of the network.

DreamDIAlignR improves DIA proteomics analysis by integrating cross-run peptide data with deep learning and FDR control, increasing detected quantitatively changing proteins by 25.6% on a benchmark dataset.

The paper constructs a genome-scale genetic interaction network from 4 million double mutants in HAP1 cells, revealing conserved genetic network principles across species and uncovering novel gene functions and cancer dependencies.

The paper shows that stress granules sequester the CCR4-NOT complex, leading to poly(A) tail lengthening and increased survival transcript abundance under stress.

This paper introduces DeepMet, a chemical language model that predicts and discovers unknown metabolites using mass spectrometry data.

This study identifies two quorum-sensing systems in E. faecalis that regulate purine biosynthesis, enhancing its pathogenicity in macrophages and murine infections.

MassDash provides a web-based tool for visualizing and validating DIA mass spectrometry data across multiple software tools.

This study shows that bacterial ADP-heptose triggers a revival stem cell program in the intestinal epithelium by inducing Paneth cell dedifferentiation and ISC loss.

DIAlignR improves quantification consistency in DIA proteomics data across multiple LC-MS/MS instruments, reducing identification errors and increasing significant protein detection.

The paper compares LSTM, CNN, and transformer models for predicting retention time and collisional cross section in mass spectrometry data, finding LSTM and CNN perform similarly while the transformer underperforms.

The paper provides a Galaxy-based pipeline for DIA proteomics analysis, enabling reproducible and accessible processing through a web interface.

This paper demonstrates that Trapped Ion Mobility Spectrometry (TIMS) reduces cofragmentation rates in mass spectrometry-based proteomics, increasing peptide identification rates.

This paper introduces a data-driven method to detect functional proteoform groups from bottom-up proteomic datasets, identifying state-specific proteoform groups linked to molecular mechanisms.

The paper evaluates metabolomics assay specificity using simulations and shows DIA outperforms MS1 and MRM in unique compound detection.

The paper describes an open-source workflow for peptide-level quantitation from DIA/SWATH-MS data using Docker-based containerization.

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.

DrawAlignR provides interactive visualization of chromatogram alignments for DIA/SWATH data and includes a faster C++ alignment algorithm.

The paper introduces a new DIA scan mode that improves peptide precursor ion sampling and identification specificity using ion mobility, achieving high proteome coverage and accuracy.

DIAlignR improves retention time alignment in SWATH-MS data by aligning raw MS2 chromatograms, outperforming existing methods and reducing alignment error significantly.

The paper assesses exome sequencing in a healthy cohort to determine the frequency of medically actionable and non-actionable findings, finding 17% had actionable variants, including some outside standard guidelines.