Cargando…
Deep Neural Network Framework Based on Word Embedding for Protein Glutarylation Sites Prediction
In recent years, much research has found that dysregulation of glutarylation is associated with many human diseases, such as diabetes, cancer, and glutaric aciduria type I. Therefore, glutarylation identification and characterization are essential tasks for determining modification-specific proteomi...
Autores principales: | Liu, Chuan-Ming, Ta, Van-Dai, Le, Nguyen Quoc Khanh, Tadesse, Direselign Addis, Shi, Chongyang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410500/ https://www.ncbi.nlm.nih.gov/pubmed/36013392 http://dx.doi.org/10.3390/life12081213 |
Ejemplares similares
-
TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
por: Nguyen, Trinh-Trung-Duong, et al.
Publicado: (2020) -
Identifying SNAREs by Incorporating Deep Learning Architecture and Amino Acid Embedding Representation
por: Le, Nguyen Quoc Khanh, et al.
Publicado: (2019) -
Computational Identification of Lysine Glutarylation Sites Using Positive-Unlabeled Learning
por: Ju, Zhe, et al.
Publicado: (2020) -
A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification
por: Le, Nguyen Quoc Khanh, et al.
Publicado: (2020) -
Functions and Mechanisms of Lysine Glutarylation in Eukaryotes
por: Xie, Longxiang, et al.
Publicado: (2021)