Machine Learning to Detect Alzheimer’s Disease from Circulating Non-coding RNAs

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previous...

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Detalles Bibliográficos
Autores principales: Ludwig, Nicole, Fehlmann, Tobias, Kern, Fabian, Gogol, Manfred, Maetzler, Walter, Deutscher, Stephanie, Gurlit, Simone, Schulte, Claudia, von Thaler, Anna-Katharina, Deuschle, Christian, Metzger, Florian, Berg, Daniela, Suenkel, Ulrike, Keller, Verena, Backes, Christina, Lenhof, Hans-Peter, Meese, Eckart, Keller, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Original research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943763/
https://www.ncbi.nlm.nih.gov/pubmed/31809862
http://dx.doi.org/10.1016/j.gpb.2019.09.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943763/
https://www.ncbi.nlm.nih.gov/pubmed/31809862
http://dx.doi.org/10.1016/j.gpb.2019.09.004

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