Type 1 Diabetes: Current Advances in High-Throughput Technologies and Computational Biology for Biomarker Studies
Biomarkers are essential for the identification of high-risk populations as well as the monitoring of preventive and therapeutic outcomes for type 1 diabetes (T1D). In this chapter, we will discuss the progress made in T1D biomarker discovery using high throughput genomic, transcriptomic, and proteo...
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| Autores principales: | , , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
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IntechOpen
2022
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/84154 |
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| Sumario: | Biomarkers are essential for the identification of high-risk populations as well as the monitoring of preventive and therapeutic outcomes for type 1 diabetes (T1D). In this chapter, we will discuss the progress made in T1D biomarker discovery using high throughput genomic, transcriptomic, and proteomic technologies collectively called as omic technologies. We also discuss the potential of artificial intelligence and omics data in the early prediction of T1D. Readers will gain an overview of the status of T1D biomarkers based on omic technologies. High throughput omic technologies combined with computational biology offer great opportunities for biomarker discovery. As we move forward, the utilization of a biomarker panel for the prediction and prevention of T1D is needed. |
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| ISBN: | 978-1-80356-395-4 |
| DOI: | 10.5772/intechopen.108248 |