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The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM
2016
Computational and Mathematical Methods in Medicine
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 ensemble learning to improve the support vector machine to process the generated protein-ligand interaction fingerprint (IFP). By combining multiple classifiers, ensemble learning is able to avoid
doi:10.1155/2016/4809831
pmid:27127534
pmcid:PMC4834164
fatcat:gdn2ltxidnegflqverndnaenwu