Cargando…
DeepACP: A Novel Computational Approach for Accurate Identification of Anticancer Peptides by Deep Learning Algorithm
Cancer is one of the most dangerous diseases to human health. The accurate prediction of anticancer peptides (ACPs) would be valuable for the development and design of novel anticancer agents. Current deep neural network models have obtained state-of-the-art prediction accuracy for the ACP classific...
Autores principales: | Yu, Lezheng, Jing, Runyu, Liu, Fengjuan, Luo, Jiesi, Li, Yizhou |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Gene & Cell Therapy
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658571/ https://www.ncbi.nlm.nih.gov/pubmed/33230481 http://dx.doi.org/10.1016/j.omtn.2020.10.005 |
Ejemplares similares
-
The applications of deep learning algorithms on in silico druggable proteins identification
por: Yu, Lezheng, et al.
Publicado: (2022) -
Systematic Analysis and Accurate Identification of DNA N4-Methylcytosine Sites by Deep Learning
por: Yu, Lezheng, et al.
Publicado: (2022) -
DeepT3_4: A Hybrid Deep Neural Network Model for the Distinction Between Bacterial Type III and IV Secreted Effectors
por: Yu, Lezheng, et al.
Publicado: (2021) -
DeepT3 2.0: improving type III secreted effector predictions by an integrative deep learning framework
por: Jing, Runyu, et al.
Publicado: (2021) -
EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework
por: Yu, Lezheng, et al.
Publicado: (2023)