Cargando…
Classification of microarray data using gene networks
BACKGROUND: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results...
Autores principales: | Rapaport, Franck, Zinovyev, Andrei, Dutreix, Marie, Barillot, Emmanuel, Vert, Jean-Philippe |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1797191/ https://www.ncbi.nlm.nih.gov/pubmed/17270037 http://dx.doi.org/10.1186/1471-2105-8-35 |
Ejemplares similares
-
Classification of arrayCGH data using fused SVM
por: Rapaport, Franck, et al.
Publicado: (2008) -
Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization
por: Boeva, Valentina, et al.
Publicado: (2011) -
NetNorM: Capturing cancer-relevant information in somatic exome mutation data with gene networks for cancer stratification and prognosis
por: Le Morvan, Marine, et al.
Publicado: (2017) -
DeDaL: Cytoscape 3 app for producing and morphing data-driven and structure-driven network layouts
por: Czerwinska, Urszula, et al.
Publicado: (2015) -
NaviCom: a web application to create interactive molecular network portraits using multi-level omics data
por: Dorel, Mathurin, et al.
Publicado: (2017)