Cargando…
Classification and prediction for multi-cancer data with ultrahigh-dimensional gene expressions
Analysis of gene expression data is an attractive topic in the field of bioinformatics, and a typical application is to classify and predict individuals’ diseases or tumors by treating gene expression values as predictors. A primary challenge of this study comes from ultrahigh-dimensionality, which...
Autor principal: | Chen, Li-Pang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477337/ https://www.ncbi.nlm.nih.gov/pubmed/36107929 http://dx.doi.org/10.1371/journal.pone.0274440 |
Ejemplares similares
-
BOOME: A Python package for handling misclassified disease and ultrahigh-dimensional error-prone gene expression data
por: Chen, Li-Pang
Publicado: (2022) -
Conditional screening for ultrahigh-dimensional survival data in case-cohort studies
por: Zhang, Jing, et al.
Publicado: (2021) -
Computationally scalable regression modeling for ultrahigh-dimensional omics data with ParProx
por: Ko, Seyoon, et al.
Publicado: (2021) -
Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis
por: Ueki, Masao, et al.
Publicado: (2012) -
Deep learning approach for cancer subtype classification using high-dimensional gene expression data
por: Shen, Jiquan, et al.
Publicado: (2022)