Cargando…
Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins i...
Autores principales: | Lin, HH, Han, LY, Zhang, HL, Zheng, CJ, Xie, B, Cao, ZW, Chen, YZ |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2006
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1764469/ https://www.ncbi.nlm.nih.gov/pubmed/17254297 http://dx.doi.org/10.1186/1471-2105-7-S5-S13 |
Ejemplares similares
-
Prediction of DNA-binding protein based on statistical and geometric features and support vector machines
por: Zhou, Weiqiang, et al.
Publicado: (2011) -
Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation
por: Xu, Ruifeng, et al.
Publicado: (2015) -
Support Vector Machine Implementations for Classification & Clustering
por: Winters-Hilt, Stephen, et al.
Publicado: (2006) -
Analysis of alcoholism data using support vector machines
por: Yu, Robert, et al.
Publicado: (2005) -
Accurate splice site prediction using support vector machines
por: Sonnenburg, Sören, et al.
Publicado: (2007)