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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
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 |
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