Cargando…
Interpretable and accurate prediction models for metagenomics data
BACKGROUND: Microbiome biomarker discovery for patient diagnosis, prognosis, and risk evaluation is attracting broad interest. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive model...
Autores principales: | Prifti, Edi, Chevaleyre, Yann, Hanczar, Blaise, Belda, Eugeni, Danchin, Antoine, Clément, Karine, Zucker, Jean-Daniel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062144/ https://www.ncbi.nlm.nih.gov/pubmed/32150601 http://dx.doi.org/10.1093/gigascience/giaa010 |
Ejemplares similares
-
Exploring Semi-Quantitative Metagenomic Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol
por: Alili, Rohia, et al.
Publicado: (2021) -
Spectral consensus strategy for accurate reconstruction of large biological networks
por: Affeldt, Séverine, et al.
Publicado: (2016) -
Biological interpretation of deep neural network for phenotype prediction based on gene expression
por: Hanczar, Blaise, et al.
Publicado: (2020) -
Protein supplementation during an energy-restricted diet induces visceral fat loss and gut microbiota amino acid metabolism activation: a randomized trial
por: Bel Lassen, Pierre, et al.
Publicado: (2021) -
Assessment of deep learning and transfer learning for cancer prediction based on gene expression data
por: Hanczar, Blaise, et al.
Publicado: (2022)