Cargando…
DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites
BACKGROUND: Addressing the laborious nature of traditional biological experiments by using an efficient computational approach to analyze RNA-binding proteins (RBPs) binding sites has always been a challenging task. RBPs play a vital role in post-transcriptional control. Identification of RBPs bindi...
Autores principales: | Zhang, Jidong, Liu, Bo, Wang, Zhihan, Lehnert, Klaus, Gahegan, Mark |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241231/ https://www.ncbi.nlm.nih.gov/pubmed/35768792 http://dx.doi.org/10.1186/s12859-022-04798-5 |
Ejemplares similares
-
A deep graph convolutional neural network architecture for graph classification
por: Zhou, Yuchen, et al.
Publicado: (2023) -
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
por: Wang, Shui-Hua, et al.
Publicado: (2021) -
Co-embedding of edges and nodes with deep graph convolutional neural networks
por: Zhou, Yuchen, et al.
Publicado: (2023) -
Predicting enhancers with deep convolutional neural networks
por: Min, Xu, et al.
Publicado: (2017) -
Breast cancer detection: Shallow convolutional neural network against deep convolutional neural networks based approach
por: Das, Himanish Shekhar, et al.
Publicado: (2023)