The purpose of this study was to implement machine learning algorithms on multiple cardiac biomarkers as a means for predicting diabetes mellitus development.
| Accession | PRJNA520920 |
| Data Type | Raw sequence reads |
| Scope | Multispecies |
| Grants | - "Genomics Core" (Grant ID P20 GM103434, National Institute of General Medical Sciences)
- "miRNA Regulation of the Mitochondrial Genome" (Grant ID R01 HL128485, National Heart, Lung, and Blood Institute)
- "Type 2 Diabetes Research" (Grant ID N/A, Community Foundation for the Ohio Valley Whipkey Trust)
- "Mitochondrial microRNA Import and Regulation" (Grant ID AHA-17PRE33660333, American Heart Association)
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| Submission | Registration date: 4-Feb-2019
West Virginia University |
| Relevance | Medical |
Project Data:
| Resource Name | Number
of Links |
|---|
| Sequence data |
| SRA Experiments | 96 |
| Other datasets |
| BioSample | 96 |