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المؤلفRabbani, Naila
تاريخ الإتاحة2023-10-11T09:46:47Z
تاريخ النشر2022-04-21
اسم المنشورInternational Journal of Molecular Sciences
المعرّفhttp://dx.doi.org/10.3390/ijms23094584
الاقتباسRabbani, N. (2022). AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics. International Journal of Molecular Sciences, 23(9), 4584.
الرقم المعياري الدولي للكتاب1661-6596
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85128382942&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/48446
الملخصProtein damage by glycation, oxidation and nitration is a continuous process in the physiological system caused by reactive metabolites associated with dicarbonyl stress, oxidative stress and nitrative stress, respectively. The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. The method of quantitation is stable isotopic dilution analysis liquid chromatography—tandem mass spec-trometry (LC-MS/MS). This provides robust quantitation of normal and damaged or modified amino acids concurrently. AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.
راعي المشروعThis research was funded by Qatar University, grant number QUHI-CMED-21/22-1.
اللغةen
الناشرMultidisciplinary Digital Publishing Institute (MDPI)
الموضوعAGEomics
Alzheimer’s disease
arthritis
autism
diabetes
glycation
machine learning
Parkinson’s disease
العنوانAGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics
النوعArticle
رقم العدد9
رقم المجلد23
ESSN1422-0067
dc.accessType Open Access


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