Cargando…
Prediction of relative solvent accessibility by support vector regression and best-first method
Since, it is believed that the native structure of most proteins is defined by their sequences, utilizing data mining methods to extract hidden knowledge from protein sequences, are unavoidable. A major difficulty in mining bioinformatics data is due to the size of the datasets which contain frequen...
Autores principales: | Meshkin, Alireza, Ghafuri, Hossein |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Leibniz Research Centre for Working Environment and Human Factors
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5698889/ https://www.ncbi.nlm.nih.gov/pubmed/29255385 |
Ejemplares similares
-
Scatter-search with support vector machine for prediction of relative solvent accessibility
por: Kashefi, Amir Hosein, et al.
Publicado: (2013) -
Comparing logistic regression, support vector machines, and permanental classification methods in predicting hypertension
por: Huang, Hsin-Hsiung, et al.
Publicado: (2014) -
Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression
por: Goli, Shahrbanoo, et al.
Publicado: (2016) -
In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression
por: Lee, Ming-Han, et al.
Publicado: (2020) -
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression
por: Mohr, Ryan, et al.
Publicado: (2020)