Identification of Microbial Strains via 2D Cross-Correlation of LC-MS Data.

ABSTRACT: Mass spectrometry is commonly used in the identification of species present in microbial samples, but the high similarity in the peptide composition between strains of a single species has made analysis at the subspecies level challenging. Prior research in this area has employed methods such as Principal Component Analysis (PCA), the k-Nearest Neighbors' (kNN) algorithm, and Pearson correlation. Previously, 1D cross-correlation of mass spectra has been shown to be useful in the classification of small molecule compounds as well as in the identification of peptide sequences via the SEQUEST algorithm and its variants. While direct application of cross-correlation to mass spectral data has been shown to aid in the identification of many other types of compounds, this type of analysis has not

SUBMITTER: Collins TJ 

PROVIDER: S-EPMC11197091 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature