Cargando…
Prediction of DNA Methylation based on Multi-dimensional feature encoding and double convolutional fully connected convolutional neural network
DNA methylation takes on critical significance to the regulation of gene expression by affecting the stability of DNA and changing the structure of chromosomes. DNA methylation modification sites should be identified, which lays a solid basis for gaining more insights into their biological functions...
Autores principales: | Hu, Wenxing, Guan, Lixin, Li, Mengshan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10461834/ https://www.ncbi.nlm.nih.gov/pubmed/37639434 http://dx.doi.org/10.1371/journal.pcbi.1011370 |
Ejemplares similares
-
Fisher encoding of convolutional neural network features for endoscopic image classification
por: Wimmer, Georg, et al.
Publicado: (2018) -
Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks
por: Scholz, Veronika, et al.
Publicado: (2021) -
Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks
por: Dong, Jie, et al.
Publicado: (2022) -
Neural encoding with unsupervised spiking convolutional neural network
por: Wang, Chong, et al.
Publicado: (2023) -
A lncRNA-disease association prediction model based on the two-step PU learning and fully connected neural networks
por: Biyu, Hou, et al.
Publicado: (2023)