Cargando…
The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM
Using the theory of machine learning to assist the virtual screening (VS) has been an effective plan. However, the quality of the training set may reduce because of mixing with the wrong docking poses and it will affect the screening efficiencies. To solve this problem, we present a method using the...
Autores principales: | Wang, Meng-yu, Li, Peng, Qiao, Pei-li |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4834164/ https://www.ncbi.nlm.nih.gov/pubmed/27127534 http://dx.doi.org/10.1155/2016/4809831 |
Ejemplares similares
-
AdaBoost-based multiple SVM-RFE for classification of mammograms in DDSM
por: Yoon, Sejong, et al.
Publicado: (2009) -
Adaboost-SVM-based probability algorithm for the prediction of all mature miRNA sites based on structured-sequence features
por: Wang, Ying, et al.
Publicado: (2019) -
Axis-Guided Vessel Segmentation Using a Self-Constructing Cascade-AdaBoost-SVM Classifier
por: Hu, Xin, et al.
Publicado: (2018) -
Classification of 5-HT(1A) Receptor Ligands on the Basis of Their Binding Affinities by Using PSO-Adaboost-SVM
por: Cheng, Zhengjun, et al.
Publicado: (2009) -
Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model
por: Liang, Jing-Wei, et al.
Publicado: (2019)