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Latent-space embedding of expression data identifies gene signatures from sputum samples of asthmatic patients
BACKGROUND: The pathogenesis of asthma is a complex process involving multiple genes and pathways. Identifying biomarkers from asthma datasets, especially those that include heterogeneous subpopulations, is challenging. Potentially, autoencoders provide ideal frameworks for such tasks as they can em...
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| Publicado no: | BMC Bioinformatics |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7560063/ https://ncbi.nlm.nih.gov/pubmed/33059594 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03785-y |
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