Improving Spectral Similarity and Molecular Network Reliability through Noise Signal Filtering in MS/MS Spectra.

ABSTRACT: In mass spectrometry, fragmentation spectra play a central role in compound identification. However, noise in MS/MS spectra can significantly impact similarity scores and molecular network (MN) reliability, leading to inaccurate compound annotation in untargeted metabolomics. This work investigates the influence of noise on MS/MS similarity scores and molecular network structure. Noise elimination increased similarity scores for homologous spectra, enhancing match affordability. In MNs, effective noise management improved network structure, resulting in more interpretable networks with fewer edges and enhanced clustering, decreasing false-positive connections. To quantitatively assess these improvements, a minimum spanning tree (MST) analysis was performed, revealing denser regions in the

SUBMITTER: Dalla Valle N 

PROVIDER: S-EPMC12311886 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature