Prediction of antimicrobial peptides based on sequence alignment and feature selection methods.
Antimicrobial peptides (AMPs) represent a class of natural peptides that form a part of the innate immune system, and this kind of 'nature's antibiotics' is quite promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop an...
Guardado en:
Autores principales: | Ping Wang, Lele Hu, Guiyou Liu, Nan Jiang, Xiaoyun Chen, Jianyong Xu, Wen Zheng, Li Li, Ming Tan, Zugen Chen, Hui Song, Yu-Dong Cai, Kuo-Chen Chou |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2011
|
Materias: | |
Acceso en línea: | https://doaj.org/article/29d0f8518777498a9c244c767cfd4183 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Stage-resolved Hi-C analyses reveal meiotic chromosome organizational features influencing homolog alignment
por: Wu Zuo, et al.
Publicado: (2021) -
The lexicon of antimicrobial peptides: a complete set of arginine and tryptophan sequences
por: Sam Clark, et al.
Publicado: (2021) -
Predicting Antimicrobial Resistance Using Partial Genome Alignments
por: D. Aytan-Aktug, et al.
Publicado: (2021) -
Multi-label Learning for Predicting the Activities of Antimicrobial Peptides
por: Pu Wang, et al.
Publicado: (2017) -
Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks.
por: Tao Huang, et al.
Publicado: (2010)