Cargando…
Protein–protein interaction prediction based on ordinal regression and recurrent convolutional neural networks
BACKGROUND: Protein protein interactions (PPIs) are essential to most of the biological processes. The prediction of PPIs is beneficial to the understanding of protein functions and thus is helpful to pathological analysis, disease diagnosis and drug design etc. As the amount of protein data is grow...
Autores principales: | Xu, Weixia, Gao, Yangyun, Wang, Yang, Guan, Jihong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501564/ https://www.ncbi.nlm.nih.gov/pubmed/34625020 http://dx.doi.org/10.1186/s12859-021-04369-0 |
Ejemplares similares
-
Identifying essential proteins from protein–protein interaction networks based on influence maximization
por: Xu, Weixia, et al.
Publicado: (2022) -
GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction
por: Elbasani, Ermal, et al.
Publicado: (2022) -
Multilabel convolution neural network for facial expression recognition and ordinal intensity estimation
por: Ekundayo, Olufisayo, et al.
Publicado: (2021) -
Genomic-Enabled Prediction of Ordinal Data with Bayesian Logistic Ordinal Regression
por: Montesinos-López, Osval A., et al.
Publicado: (2015) -
Predicting happiness levels of European immigrants and natives: An application of Artificial Neural Network and Ordinal Logistic Regression
por: Chen, Shaoming, et al.
Publicado: (2022)