Cargando…
Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences
Machine learning based predictions of protein–protein interactions (PPIs) could provide valuable insights into protein functions, disease occurrence, and therapy design on a large scale. The intensive feature engineering in most of these methods makes the prediction task more tedious and trivial. Th...
Autores principales: | Li, Hang, Gong, Xiu-Jun, Yu, Hua, Zhou, Chang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6222503/ https://www.ncbi.nlm.nih.gov/pubmed/30071670 http://dx.doi.org/10.3390/molecules23081923 |
Ejemplares similares
-
On the prediction of DNA-binding proteins only from primary sequences: A deep learning approach
por: Qu, Yu-Hui, et al.
Publicado: (2017) -
Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree
por: Zhou, Chang, et al.
Publicado: (2017) -
Graph Neural Network for Protein–Protein Interaction Prediction: A Comparative Study
por: Zhou, Hang, et al.
Publicado: (2022) -
Prediction of Protein–Protein Interactions in Arabidopsis, Maize, and Rice by Combining Deep Neural Network With Discrete Hilbert Transform
por: Pan, Jie, et al.
Publicado: (2021) -
A Survey on Deep Networks Approaches in Prediction of Sequence-Based Protein–Protein Interactions
por: Mewara, Bhawna, et al.
Publicado: (2022)