Modeling transcriptomic age using knowledge-primed artificial neural networks

The development of ‘age clocks’, machine learning models predicting age from biological data, has been a major milestone in the search for reliable markers of biological age and has since become an invaluable tool in aging research. However, beyond their unquestionable utility, current clocks offer...

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Detalles Bibliográficos
Autores principales: Holzscheck, Nicholas, Falckenhayn, Cassandra, Söhle, Jörn, Kristof, Boris, Siegner, Ralf, Werner, André, Schössow, Janka, Jürgens, Clemens, Völzke, Henry, Wenck, Horst, Winnefeld, Marc, Grönniger, Elke, Kaderali, Lars
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169742/
https://www.ncbi.nlm.nih.gov/pubmed/34075044
http://dx.doi.org/10.1038/s41514-021-00068-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169742/
https://www.ncbi.nlm.nih.gov/pubmed/34075044
http://dx.doi.org/10.1038/s41514-021-00068-5

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