Cargando…
ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions
The increasing number of genome-wide assays of gene expression available from public databases presents opportunities for computational methods that facilitate hypothesis generation and biological interpretation of these data. We present an unsupervised machine learning approach, ADAGE (analysis usi...
Autores principales: | Tan, Jie, Hammond, John H., Hogan, Deborah A., Greene, Casey S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Microbiology
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069748/ https://www.ncbi.nlm.nih.gov/pubmed/27822512 http://dx.doi.org/10.1128/mSystems.00025-15 |
Ejemplares similares
-
ADAGE signature analysis: differential expression analysis with data-defined gene sets
por: Tan, Jie, et al.
Publicado: (2017) -
435: Investigating the effect of host- and microbe-mediated zinc chelation on Pseudomonas aeruginosa in cystic fibrosis sputum
por: Vermilyea, D., et al.
Publicado: (2021) -
Sparse Convolutional Denoising Autoencoders for Genotype Imputation
por: Chen, Junjie, et al.
Publicado: (2019) -
Denoising of Optics Measurements Using Autoencoder Neural Networks
por: Fol, Elena, et al.
Publicado: (2021) -
Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder
por: Li, Zexin, et al.
Publicado: (2020)