Cargando…
Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously
Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now the platform of choice for many new experiments. The data structure and distributions between the pla...
Autores principales: | Foltz, Steven M., Greene, Casey S., Taroni, Jaclyn N. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9968332/ https://www.ncbi.nlm.nih.gov/pubmed/36841852 http://dx.doi.org/10.1038/s42003-023-04588-6 |
Ejemplares similares
-
Cross-platform normalization of microarray and RNA-seq data for machine learning applications
por: Thompson, Jeffrey A., et al.
Publicado: (2016) -
Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm
por: Romero, Juan P., et al.
Publicado: (2018) -
Seq-ing improved gene expression estimates from microarrays using machine learning
por: Korir, Paul K., et al.
Publicado: (2015) -
Rank-in: enabling integrative analysis across microarray and RNA-seq for cancer
por: Tang, Kailin, et al.
Publicado: (2021) -
Classification of microarrays; synergistic effects between normalization, gene selection and machine learning
por: Önskog, Jenny, et al.
Publicado: (2011)