Cargando…
Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data
BACKGROUND: High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biol...
Autores principales: | Reshetova, Polina, Smilde, Age K, van Kampen, Antoine HC, Westerhuis, Johan A |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101693/ https://www.ncbi.nlm.nih.gov/pubmed/25033193 http://dx.doi.org/10.1186/1752-0509-8-S2-S2 |
Ejemplares similares
-
Metabolic network discovery through reverse engineering of metabolome data
por: Çakır, Tunahan, et al.
Publicado: (2009) -
Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies
por: Szymańska, Ewa, et al.
Publicado: (2011) -
Centering, scaling, and transformations: improving the biological information content of metabolomics data
por: van den Berg, Robert A, et al.
Publicado: (2006) -
Fusing metabolomics data sets with heterogeneous measurement errors
por: Waaijenborg, Sandra, et al.
Publicado: (2018) -
Analysis of high-dimensional metabolomics data with complex temporal dynamics using RM-ASCA+
por: Erdős, Balázs, et al.
Publicado: (2023)