Abstract
Changes in biological pathways provide essential clues about metabolism.
Genome-scale metabolic Models (GEM) are network-based templates that
computationally describe all stoichiometric associations and
gene-protein reaction (GPR) relations found in an organism for all its
metabolic genes and metabolites. Using reaction stoichiometry as input,
GEMs mathematically simulate metabolic reaction fluxes occurring in an
organism and predict changes in the metabolic system under the relevant
condition. Multiple tools and approaches in the literature can capture
fluxes sensitive to a given condition by using GEMs. However, functional
enrichment analysis of these reaction lists in a systems biology
perspective is not straightforward. Here, we introduce RSEA to annotate
given reaction sets to significantly related metabolic pathways:
Reaction Set Enrichment Analysis web server tool. RSEA converts given
reaction list derived from GEMs into proper reaction identifiers and
statistically analyze its enrichment in metabolic pathways. RSEA is
designed to provide researchers with a practical and user-friendly
platform to explore and interpret sets of reactions in biological
pathways and freely available online (https://rseatool.com/).