Cargando…
GSPHI: A novel deep learning model for predicting phage-host interactions via multiple biological information
Emerging evidence suggests that due to the misuse of antibiotics, bacteriophage (phage) therapy has been recognized as one of the most promising strategies for treating human diseases infected by antibiotic-resistant bacteria. Identification of phage-host interactions (PHIs) can help to explore the...
Autores principales: | Pan, Jie, You, Wencai, Lu, Xiaoliang, Wang, Shiwei, You, Zhuhong, Sun, Yanmei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314231/ https://www.ncbi.nlm.nih.gov/pubmed/37397626 http://dx.doi.org/10.1016/j.csbj.2023.06.014 |
Ejemplares similares
-
A Novel Ensemble Learning-Based Computational Method to Predict Protein-Protein Interactions from Protein Primary Sequences
por: Pan, Jie, et al.
Publicado: (2022) -
Ensemble Learning Prediction of Drug-Target Interactions Using GIST Descriptor Extracted from PSSM-Based Evolutionary Information
por: Zhan, Xinke, et al.
Publicado: (2020) -
A deep learning framework for identifying essential proteins based on multiple biological information
por: Yue, Yi, et al.
Publicado: (2022) -
Genomic insights into phage-host interaction in the deep-sea chemolithoautotrophic Campylobacterota, Nitratiruptor
por: Yoshida-Takashima, Yukari, et al.
Publicado: (2022) -
Deciphering Phage-Host Specificity Based on the Association of Phage Depolymerases and Bacterial Surface Glycan with Deep Learning
por: Yang, Yiyan, et al.
Publicado: (2023)