Evaluation of machine-learning methods for ligand-based virtual screening
نویسندگان
چکیده
منابع مشابه
Evaluation of machine-learning methods for ligand-based virtual screening
Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it ...
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In silico High Throughput Screening of large compound databases has become increasingly popular technology of finding valuable drug candidates, by applying a wide range of computational methods, such as machine learning [1]. In recent years, many comparative studies of different machine learning methods performance in ligandbased virtual screening have been reported [2,3]. In order to extend th...
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BACKGROUND Ligand-based virtual screening experiments are an important task in the early drug discovery stage. An ambitious aim in each experiment is to disclose active structures based on new scaffolds. To perform these "scaffold-hoppings" for individual problems and targets, a plethora of different similarity methods based on diverse techniques were published in the last years. The optimal as...
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ژورنال
عنوان ژورنال: Journal of Computer-Aided Molecular Design
سال: 2007
ISSN: 0920-654X,1573-4951
DOI: 10.1007/s10822-006-9096-5