Joe Wandy

Large-scale discovery and annotation of hidden substructure patterns in mass spectrometry profiles

The paper improves MS2LDA for substructure discovery in mass spectrometry by enhancing speed and introducing automated annotation guidance, validated on chemical datasets.

Comprehensive LC-MS/MS Data Acquisition in Metabolomics via Maximum Bipartite Matching

The paper introduces a maximum bipartite matching workflow for LC-MS/MS data acquisition to improve the identification of metabolites by optimizing fragmentation spectra collection.

TopNEXt: Automatic DDA Exclusion Framework for Multi-Sample Mass Spectrometry Experiments

TopNEXt improves data acquisition in multi-sample LC-MS/MS metabolomics by extending DDA exclusion methods across samples using a Region of Interest and intensity-based scoring system.

Simulated-to-real Benchmarking of Acquisition Methods in Metabolomics

This study benchmarks DDA and DIA acquisition methods in metabolomics using simulations and real-world validation, showing performance differences based on co-eluting ion counts.

GraphOmics: an Interactive Platform to Explore and Integrate Multi-Omics Data

GraphOmics integrates multi-omics data through pathway mapping and interactive exploration to support hypothesis generation.

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions

The paper introduces NPLinker, a framework that combines scoring functions to link microbial genomic and metabolomic data, improving identification of biosynthetic gene clusters and their associated metabolites.

Rapid Development of Improved Data-dependent Acquisition Strategies.

This paper develops new data-dependent acquisition strategies for metabolomics using an in silico framework, showing they fragment more unique ions than standard methods.

Decomposing metabolite set activity levels with PALS

PALS ranks significantly changing metabolite sets across conditions, showing robustness to missing data in metabolomics analyses.

In-silico Optimisation of Mass Spectrometry Fragmentation Strategies in Metabolomics

The paper introduces ViMMS, a simulator for LC-MS/MS fragmentation strategies, enabling in-silico testing and optimization of mass spectrometry acquisition methods.

Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra

This paper introduces methods to improve metabolite annotation using substructure discovery and machine learning, along with a database for shared motifs.

HDP-Align: Hierarchical Dirichlet Process Clustering for Multiple Peak Alignment of Liquid Chromatography Mass Spectrometry Data.

HDP-Align aligns peaks across multiple LC-MS runs using a Bayesian non-parametric model, providing confidence scores for alignment results.