Year: 2025
Type: article
Abstract: MOTIVATION: Untargeted metabolomics involves a large-scale comparison of the fragmentation pattern of a mass spectrum against a database containing known spectra. Given the number of comparisons involved, this step can be time-consuming. RESULTS: In this work, we present a GPU-accelerated cosine similarity implementation for Tandem Mass Spectrometry (MS), with an approximately 1000-fold speedup compared to the MatchMS reference implementation, without any loss of accuracy. This improvement enables repository-scale spectral library matching for compound identification without the need for large compute clusters. This impact extends to any spectral comparison-based methods such as molecular networking approaches and analogue search. AVAILABILITY AND IMPLEMENTATION: All code, results, and notebooks supporting are freely available under the MIT license at https://github.com/pangeAI/simms/.
Source: Bioinformatics
Institution: Max Planck Unit for the Science of Pathogens
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,989
OpenAlex ID: W4407762022