Cargando…
Discovering combinatorial interactions in survival data
Motivation: Although several methods exist to relate high-dimensional gene expression data to various clinical phenotypes, finding combinations of features in such input remains a challenge, particularly when fitting complex statistical models such as those used for survival studies. Results: Our pr...
Autores principales: | duVerle, David A., Takeuchi, Ichiro, Murakami-Tonami, Yuko, Kadomatsu, Kenji, Tsuda, Koji |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3834797/ https://www.ncbi.nlm.nih.gov/pubmed/24037215 http://dx.doi.org/10.1093/bioinformatics/btt532 |
Ejemplares similares
-
CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data
por: duVerle, David A., et al.
Publicado: (2016) -
Nucleolar protein PES1 is a marker of neuroblastoma outcome and is associated with neuroblastoma differentiation
por: Nakaguro, Masato, et al.
Publicado: (2015) -
SMG6 regulates DNA damage and cell survival in Hippo pathway kinase LATS2-inactivated malignant mesothelioma
por: Suzuki, Koya, et al.
Publicado: (2022) -
Inactivation of SMC2 shows a synergistic lethal response in MYCN-amplified neuroblastoma cells
por: Murakami-Tonami, Yuko, et al.
Publicado: (2014) -
Calpain Cleavage Prediction Using Multiple Kernel Learning
por: duVerle, David A., et al.
Publicado: (2011)