Cargando…
DECO: decompose heterogeneous population cohorts for patient stratification and discovery of sample biomarkers using omic data profiling
MOTIVATION: Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods s...
Autores principales: | Campos-Laborie, F J, Risueño, A, Ortiz-Estévez, M, Rosón-Burgo, B, Droste, C, Fontanillo, C, Loos, R, Sánchez-Santos, J M, Trotter, M W, De Las Rivas, J |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761977/ https://www.ncbi.nlm.nih.gov/pubmed/30824909 http://dx.doi.org/10.1093/bioinformatics/btz148 |
Ejemplares similares
-
Analyse multiple disease subtypes and build associated gene networks using genome-wide expression profiles
por: Aibar, Sara, et al.
Publicado: (2015) -
A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples
por: Risueño, Alberto, et al.
Publicado: (2014) -
Human Gene Coexpression Landscape: Confident Network Derived from Tissue Transcriptomic Profiles
por: Prieto, Carlos, et al.
Publicado: (2008) -
GATExplorer: Genomic and Transcriptomic Explorer; mapping expression probes to gene loci, transcripts, exons and ncRNAs
por: Risueño, Alberto, et al.
Publicado: (2010) -
Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering
por: Aibar, Sara, et al.
Publicado: (2015)