Cargando…
Improved Prediction Model of Protein and Peptide Toxicity by Integrating Channel Attention into a Convolutional Neural Network and Gated Recurrent Units
[Image: see text] In recent times, the importance of peptides in the biomedical domain has received increasing concern in terms of their effect on multiple disease treatments. However, before successful large-scale implementation in the industry, accurate identification of peptide toxicity is a vita...
Autores principales: | Zhao, Zhengyun, Gui, Jingyu, Yao, Anqi, Le, Nguyen Quoc Khanh, Chua, Matthew Chin Heng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9647964/ https://www.ncbi.nlm.nih.gov/pubmed/36385847 http://dx.doi.org/10.1021/acsomega.2c05881 |
Ejemplares similares
-
Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture
por: Le, Nguyen Quoc Khanh, et al.
Publicado: (2019) -
Ensemble of Deep Recurrent Neural Networks for Identifying Enhancers via Dinucleotide Physicochemical Properties
por: Tan, Kok Keng, et al.
Publicado: (2019) -
Multiscale Hybrid Convolutional Deep Neural Networks with Channel Attention
por: Yang, Hua, et al.
Publicado: (2022) -
Attention-Based Spatial–Temporal Convolution Gated Recurrent Unit for Traffic Flow Forecasting
por: Zhang, Qingyong, et al.
Publicado: (2023) -
Double attention recurrent convolution neural network for answer selection
por: Bao, Ganchao, et al.
Publicado: (2020)