Cargando…
Identification of Penicillin-binding proteins employing support vector machines and random forest
Penicillin-Binding Proteins are peptidases that play an important role in cell-wall biogenesis in bacteria and thus maintaining bacterial infections. A wide class of β-lactam drugs are known to act on these proteins and inhibit bacterial infections by disrupting the cell-wall biogenesis pathway. Pen...
Autores principales: | Nair, Vinay, Dutta, Monalisa, Manian, Sowmya S, S, Ramya Kumari, Jayaraman, Valadi K |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705620/ https://www.ncbi.nlm.nih.gov/pubmed/23847404 http://dx.doi.org/10.6026/97320630009481 |
Ejemplares similares
-
Quantitative Structure Activity Relationship study of the Anti-Hepatitis Peptides employing Random Forests and Extra-trees regressors
por: Mishra, Gunjan, et al.
Publicado: (2017) -
Prediction of protein-mannose binding sites using random forest
por: Khare, Harshvardan, et al.
Publicado: (2012) -
A text mining approach to detect mentions of protein glycosylation in biomedical text
por: Shukla, Daksha, et al.
Publicado: (2012) -
Classifying DNA repair genes by kernel-based support vector machines
por: Jiang, Hao, et al.
Publicado: (2011) -
Application of Support Vector Machines in Viral Biology
por: Modak, Sonal, et al.
Publicado: (2019)