Cargando…
Disease gene identification by random walk on multigraphs merging heterogeneous genomic and phenotype data
BACKGROUND: High throughput experiments resulted in many genomic datasets and hundreds of candidate disease genes. To discover the real disease genes from a set of candidate genes, computational methods have been proposed and worked on various types of genomic data sources. As a single source of gen...
Autores principales: | Li, Yongjin, Li, Jinyan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521411/ https://www.ncbi.nlm.nih.gov/pubmed/23282070 http://dx.doi.org/10.1186/1471-2164-13-S7-S27 |
Ejemplares similares
-
Goodness of fit tests for random multigraph models
por: Shafie, Termeh
Publicado: (2022) -
Linkage analysis merging replicate phenotypes: an application to three quantitative phenotypes in two African samples
por: Hinrichs, Anthony L, et al.
Publicado: (2011) -
Comparison of data-merging methods with SVM attribute selection and classification in breast cancer gene expression
por: Bevilacqua, Vitoantonio, et al.
Publicado: (2012) -
A Multigraph-Based Representation of Hi-C Data
por: Makai, Diána, et al.
Publicado: (2022) -
Identification of genes for complex disease using longitudinal phenotypes
por: Pankratz, Nathan, et al.
Publicado: (2003)