Cargando…
MSTL-Kace: Prediction of Prokaryotic Lysine Acetylation Sites Based on Multistage Transfer Learning Strategy
[Image: see text] As one of the most important post-translational modifications (PTM), lysine acetylation (Kace) plays an important role in various biological activities. Traditional experimental methods for identifying Kace sites are inefficient and expensive. Instead, several machine learning meth...
Autores principales: | Wang, Gang-Ao, Yan, Xiaodi, Li, Xiang, Liu, Yinbo, Xia, Junfeng, Zhu, Xiaolei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634282/ https://www.ncbi.nlm.nih.gov/pubmed/37969991 http://dx.doi.org/10.1021/acsomega.3c07086 |
Ejemplares similares
-
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction
por: Basith, Shaherin, et al.
Publicado: (2021) -
BERT-Kgly: A Bidirectional Encoder Representations From Transformers (BERT)-Based Model for Predicting Lysine Glycation Site for Homo sapiens
por: Liu, Yinbo, et al.
Publicado: (2022) -
Site-Specific Reactivity of Nonenzymatic Lysine Acetylation
por: Baeza, Josue, et al.
Publicado: (2015) -
LAIPT: Lysine Acetylation Site Identification with Polynomial Tree
por: Bao, Wenzheng, et al.
Publicado: (2018) -
An Alternative Strategy for Pan-acetyl-lysine Antibody Generation
por: Kim, Sun-Yee, et al.
Publicado: (2016)