Cargando…
Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the risk ADHD-associated variants and genes with significant P-values, they may neglect the combined effect of multiple variants with insignificant P-valu...
Autores principales: | Liu, Lu, Feng, Xikang, Li, Haimei, Cheng Li, Shuai, Qian, Qiujin, Wang, Yufeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575025/ https://www.ncbi.nlm.nih.gov/pubmed/34109382 http://dx.doi.org/10.1093/bib/bbab207 |
Ejemplares similares
-
A general optimization protocol for molecular property prediction using a deep learning network
por: Chen, Jen-Hao, et al.
Publicado: (2021) -
GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data
por: Fiannaca, Antonino, et al.
Publicado: (2023) -
Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power
por: Yu, Tzu-Hui, et al.
Publicado: (2021) -
DeepImmuno: deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity
por: Li, Guangyuan, et al.
Publicado: (2021) -
New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform
por: Chen, Hebing, et al.
Publicado: (2019)