Shiny GATOM: omics-based identification of regulated metabolic modules in atom transition networks.

ABSTRACT: Multiple high-throughput omics techniques provide different angles on systematically quantifying and studying metabolic regulation of cellular processes. However, an unbiased analysis of such data and, in particular, integration of multiple types of data remains a challenge. Previously, for this purpose we developed GAM web-service for integrative metabolic network analysis. Here we describe an updated pipeline GATOM and the corresponding web-service Shiny GATOM, which takes as input transcriptional and/or metabolomic data and finds a metabolic subnetwork most regulated between the two conditions of interest. GATOM features a new metabolic network topology based on atom transition, which significantly improves interpretability of the analysis results. To address computational challenges ar

SUBMITTER: Emelianova M 

PROVIDER: S-EPMC9252739 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature