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SimMS: a GPU-accelerated cosine similarity implementation for tandem mass spectrometry

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… Click to show full abstract

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. In this work, we present a GPU-accelerated cosine similarity implementation for Tandem Mass Spectrometry (MS) with approximately 1000-fold speedup compared to the MatchMS reference at a rate of 0.005% incorrect matches and a rate of 0.002% incorrect scores. We describe the underlying reasons for these errors and provide means to avoid them.

Keywords: gpu accelerated; cosine similarity; similarity implementation; mass; accelerated cosine; implementation tandem

Journal Title: Bioinformatics
Year Published: 2024

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