Cargando…
Variational autoencoders learn transferrable representations of metabolomics data
Dimensionality reduction approaches are commonly used for the deconvolution of high-dimensional metabolomics datasets into underlying core metabolic processes. However, current state-of-the-art methods are widely incapable of detecting nonlinearities in metabolomics data. Variational Autoencoders (V...
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9246987/ https://www.ncbi.nlm.nih.gov/pubmed/35773471 http://dx.doi.org/10.1038/s42003-022-03579-3 |