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Original Research

Application of Artificial Intelligence Modeling Technology Based on Multi-Omics in Noninvasive Diagnosis of Inflammatory Bowel Disease

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Pages 1933-1943 | Published online: 14 May 2021

References

  • Kaplan GG. The global burden of IBD: from 2015 to 2025. Nat Rev Gastroenterol Hepatol. 2015;12(12):720–727. doi:10.1038/nrgastro.2015.150
  • Sexton KA, Walker JR, Targownik LE, et al. The inflammatory bowel disease symptom inventory: a patient-report scale for research and clinical application. Inflamm Bowel Dis. 2019;25(8):1277–1290. doi:10.1093/ibd/izz038
  • Kinsey L, Burden S. A survey of people with inflammatory bowel disease to investigate their views of food and nutritional issues. Eur J Clin Nutr. 2016;70(7):852–854. doi:10.1038/ejcn.2016.57
  • Lloyd-Price J, Arze C, Ananthakrishnan AN, et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature. 2019;569(7758):655–662. doi:10.1038/s41586-019-1237-9
  • Lamb CA, Kennedy NA, Raine T, et al. British society of gastroenterology consensus guidelines on the management of inflammatory bowel disease in adults. Gut. 2019;68(Suppl 3):s1–s106. doi:10.1136/gutjnl-2019-318484
  • Mossotto E, Ashton JJ, Coelho T, Beattie RM, MacArthur BD, Ennis S. Classification of paediatric inflammatory bowel disease using machine learning. Sci Rep. 2017;7(1):2427. doi:10.1038/s41598-017-02606-2
  • Ozawa T, Ishihara S, Fujishiro M, et al. Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis. Gastrointest Endosc. 2019;89(2):416–421 e1. doi:10.1016/j.gie.2018.10.020
  • Franzosa EA, Sirota-Madi A, Avila-Pacheco J, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat Microbiol. 2019;4(2):293–305. doi:10.1038/s41564-018-0306-4
  • Oussalah A, Gueant JL, Peyrin-Biroulet L. Meta-analysis: hyperhomocysteinaemia in inflammatory bowel diseases. Aliment Pharmacol Ther. 2011;34(10):1173–1184. doi:10.1111/j.1365-2036.2011.04864.x
  • Sangshetti JN, Khan FA, Shinde DB. Peptide deformylase: a new target in antibacterial, antimalarial and anticancer drug discovery. Curr Med Chem. 2015;22(2):214–236. doi:10.2174/0929867321666140826115734
  • Leeds JA, Dean CR. Peptide deformylase as an antibacterial target: a critical assessment. Curr Opin Pharmacol. 2006;6(5):445–452. doi:10.1016/j.coph.2006.06.003
  • Proteau PJ. 1-Deoxy-D-xylulose 5-phosphate reductoisomerase: an overview. Bioorg Chem. 2004;32(6):483–493. doi:10.1016/j.bioorg.2004.08.004
  • Singh N, Cheve G, Avery MA, McCurdy CR. Targeting the methyl erythritol phosphate (MEP) pathway for novel antimalarial, antibacterial and herbicidal drug discovery: inhibition of 1-deoxy-D-xylulose-5-phosphate reductoisomerase (DXR) enzyme. Curr Pharm Des. 2007;13(11):1161–1177. doi:10.2174/138161207780618939
  • Serrano A, Ferreira P, Martinez-Julvez M, Medina M. The prokaryotic FAD synthetase family: a potential drug target. Curr Pharm Des. 2013;19(14):2637–2648. doi:10.2174/1381612811319140013
  • Gnainsky Y, Zfanya N, Elgart M, et al. Systemic regulation of host energy and oogenesis by microbiome-derived mitochondrial coenzymes. Cell Rep. 2021;34(1):108583. doi:10.1016/j.celrep.2020.108583
  • Kukko E, Saarento H. Diphosphate concentration does not correlate with the level of inorganic diphosphatase in Escherichia coli. Folia Microbiol (Praha). 1984;29(4):282–287. doi:10.1007/BF02875958
  • Vincent EE, Sergushichev A, Griss T, et al. Mitochondrial phosphoenolpyruvate carboxykinase regulates metabolic adaptation and enables glucose-independent tumor growth. Mol Cell. 2015;60(2):195–207. doi:10.1016/j.molcel.2015.08.013
  • Hornik K, Stinchcombe M, White H. Multilayer feedforward networks are universal approximators. Neural Netw. 1989;2(5):359–366. doi:10.1016/0893-6080(89)90020-8