Application of Differential Network Enrichment Analysis for Deciphering Metabolic Alterations.

ABSTRACT: Modern analytical methods allow for the simultaneous detection of hundreds of metabolites, generating increasingly large and complex data sets. The analysis of metabolomics data is a multi-step process that involves data processing and normalization, followed by statistical analysis. One of the biggest challenges in metabolomics is linking alterations in metabolite levels to specific biological processes that are disrupted, contributing to the development of disease or reflecting the disease state. A common approach to accomplishing this goal involves pathway mapping and enrichment analysis, which assesses the relative importance of predefined metabolic pathways or other biological categories. However, traditional knowledge-based enrichment analysis has limitations when it comes to the ana

SUBMITTER: Iyer GR 

PROVIDER: S-EPMC7761243 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature