Modeling transcriptomic age using knowledge-primed artificial neural networks
Abstract 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 cloc...
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/777c395850e541569fc03b8d41e94be4 |
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