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Generalizing predictions to unseen sequencing profiles via deep generative models
Predictive models trained on sequencing profiles often fail to achieve expected performance when externally validated on unseen profiles. While many factors such as batch effects, small data sets, and technical errors contribute to the gap between source and unseen data distributions, it is a challe...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065080/ https://www.ncbi.nlm.nih.gov/pubmed/35504956 http://dx.doi.org/10.1038/s41598-022-11363-w |