Cargando…
Ensemble Consensus-Guided Unsupervised Feature Selection to Identify Huntington’s Disease-Associated Genes
Due to the complexity of the pathological mechanisms of neurodegenerative diseases, traditional differentially-expressed gene selection methods cannot detect disease-associated genes accurately. Recent studies have shown that consensus-guided unsupervised feature selection (CGUFS) performs well in f...
Autores principales: | Guo, Xia, Jiang, Xue, Xu, Jing, Quan, Xiongwen, Wu, Min, Zhang, Han |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071299/ https://www.ncbi.nlm.nih.gov/pubmed/30002337 http://dx.doi.org/10.3390/genes9070350 |
Ejemplares similares
-
Identify Huntington’s disease associated genes based on restricted Boltzmann machine with RNA-seq data
por: Jiang, Xue, et al.
Publicado: (2017) -
Towards an Optimized Ensemble Feature Selection for DDoS Detection Using Both Supervised and Unsupervised Method †
por: Saha, Sajal, et al.
Publicado: (2022) -
Unsupervised encoding selection through ensemble pruning for biomedical classification
por: Spänig, Sebastian, et al.
Publicado: (2023) -
Using the Kriging Correlation for unsupervised feature selection problems
por: Chua, Cheng-Han, et al.
Publicado: (2022) -
Group Based Unsupervised Feature Selection
por: Perera, Kushani, et al.
Publicado: (2020)