miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes
miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes
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Publisher
London: BioMed Central Ltd
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Language
English
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Publisher
London: BioMed Central Ltd
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Contents
Type 2 diabetes mellitus (T2DM) affects approximately 451 million adults globally. In this study, we identified the optimal combination of marker candidates for detecting T2DM using miRNA-Seq data from 95 samples including T2DM and healthy individuals. We utilized the genetic algorithm (GA) in the discovery of an optimal miRNA biomarker set. We dis...
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Full title
miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes
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TN_cdi_doaj_primary_oai_doaj_org_article_4a25f504f5d84013a0785236d5df1768
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4a25f504f5d84013a0785236d5df1768
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ISSN
1755-8794
E-ISSN
1755-8794
DOI
10.1186/s12920-023-01636-2
