Cargando…
Classification and deep-learning–based prediction of Alzheimer disease subtypes by using genomic data
Late-onset Alzheimer’s disease (LOAD) is the most common multifactorial neurodegenerative disease among elderly people. LOAD is heterogeneous, and the symptoms vary among patients. Genome-wide association studies (GWAS) have identified genetic risk factors for LOAD but not for LOAD subtypes. Here, w...
Autores principales: | Shigemizu, Daichi, Akiyama, Shintaro, Suganuma, Mutsumi, Furutani, Motoki, Yamakawa, Akiko, Nakano, Yukiko, Ozaki, Kouichi, Niida, Shumpei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10310810/ https://www.ncbi.nlm.nih.gov/pubmed/37386009 http://dx.doi.org/10.1038/s41398-023-02531-1 |
Ejemplares similares
-
Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through immune landscape analysis
por: Shigemizu, Daichi, et al.
Publicado: (2022) -
Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data
por: Asanomi, Yuya, et al.
Publicado: (2021) -
Whole-genome sequencing reveals novel ethnicity-specific rare variants associated with Alzheimer’s disease
por: Shigemizu, Daichi, et al.
Publicado: (2022) -
Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through RNA sequencing analysis
por: Shigemizu, Daichi, et al.
Publicado: (2020) -
JAMIR-eQTL: Japanese genome-wide identification of microRNA expression
quantitative trait loci across dementia types
por: Akiyama, Shintaro, et al.
Publicado: (2021)