Suggesting disease associations for overlooked metabolites using literature from metabolic neighbors.

ABSTRACT: In human health research, metabolic signatures extracted from metabolomics data have a strong added value for stratifying patients and identifying biomarkers. Nevertheless, one of the main challenges is to interpret and relate these lists of discriminant metabolites to pathological mechanisms. This task requires experts to combine their knowledge with information extracted from databases and the scientific literature. However, we show that most compounds (>99%) in the PubChem database lack annotated literature. This dearth of available information can have a direct impact on the interpretation of metabolic signatures, which is often restricted to a subset of significant metabolites. To suggest potential pathological phenotypes related to overlooked metabolites that lack annotated literatur

SUBMITTER: Delmas M 

PROVIDER: S-EPMC10502579 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature