Cargando…
T1SEstacker: A Tri-Layer Stacking Model Effectively Predicts Bacterial Type 1 Secreted Proteins Based on C-Terminal Non-repeats-in-Toxin-Motif Sequence Features
Type 1 secretion systems play important roles in pathogenicity of Gram-negative bacteria. However, the substrate secretion mechanism remains largely unknown. In this research, we observed the sequence features of repeats-in-toxin (RTX) proteins, a major class of type 1 secreted effectors (T1SEs). We...
Autores principales: | Chen, Zewei, Zhao, Ziyi, Hui, Xinjie, Zhang, Junya, Hu, Yixue, Chen, Runhong, Cai, Xuxia, Hu, Yueming, Wang, Yejun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8861453/ https://www.ncbi.nlm.nih.gov/pubmed/35211101 http://dx.doi.org/10.3389/fmicb.2021.813094 |
Ejemplares similares
-
Computational prediction of secreted proteins in gram-negative bacteria
por: Hui, Xinjie, et al.
Publicado: (2021) -
T3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted Effectors
por: Hui, Xinjie, et al.
Publicado: (2020) -
FakeStack: Hierarchical Tri-BERT-CNN-LSTM stacked model for effective fake news detection
por: Keya, Ashfia Jannat, et al.
Publicado: (2023) -
Identification of Human Global, Tissue and Within-Tissue Cell-Specific Stably Expressed Genes at Single-Cell Resolution
por: Qiu, Lingyu, et al.
Publicado: (2022) -
Improving the diversity of captured full-length isoforms using a normalized single-molecule RNA-sequencing method
por: Hu, Yueming, et al.
Publicado: (2020)