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

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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Bibliographic Details
Main Authors: Nicole Ludwig, Tobias Fehlmann, Fabian Kern, Manfred Gogol, Walter Maetzler, Stephanie Deutscher, Simone Gurlit, Claudia Schulte, Anna-Katharina von Thaler, Christian Deuschle, Florian Metzger, Daniela Berg, Ulrike Suenkel, Verena Keller, Christina Backes, Hans-Peter Lenhof, Eckart Meese, Andreas Keller
Format: Article
Language:English
Published: Elsevier 2019-08-01
Series:Genomics, Proteomics & Bioinformatics
Online Access:http://www.sciencedirect.com/science/article/pii/S1672022919301573

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http://www.sciencedirect.com/science/article/pii/S1672022919301573

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