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RSEA: a web server for pathway enrichment analysis of metabolic reaction sets
  • +2
  • Merve Yarıcı,
  • Furkan Cantürk,
  • Serdar Dursun,
  • Hatice Nur Aydın,
  • Muhammed Erkan Karabekmez
Merve Yarıcı
Istanbul Medeniyet Universitesi Muhendislik ve Doga Bilimleri
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Furkan Cantürk
Ozyegin Universitesi
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Serdar Dursun
AVL Research and Engineering Turkey
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Hatice Nur Aydın
Istanbul Medeniyet Universitesi Muhendislik ve Doga Bilimleri
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Muhammed Erkan Karabekmez
Istanbul Medeniyet Universitesi Muhendislik ve Doga Bilimleri

Corresponding Author:[email protected]

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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/).
Submitted to Biotechnology and Bioengineering
30 Jul 2024Reviewer(s) Assigned
19 Sep 2024Review(s) Completed, Editorial Evaluation Pending
30 Sep 2024Editorial Decision: Revise Major