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Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
(Oxford Univ Press, 2019)
The identification of interactions between drugs/compounds and their targets is crucial for the development of new drugs. In vitro screening experiments (i.e. bioassays) are frequently used for this purpose; however, ...
DEEPScreen: high performance drug-target interaction prediction with convolutional neural networks using 2-D structural compound representations
(Royal Soc Chemistry, 2020)
The identification of physical interactions between drug candidate compounds and target biomolecules is an important process in drug discovery. Since conventional screening procedures are expensive and time consuming, ...
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
(Nature Publishing Group, 2019)
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed ...
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
(BMC, 2018)
Background: The automated prediction of the enzymatic functions of uncharacterized proteins is a crucial topic in bioinformatics. Although several methods and tools have been proposed to classify enzymes, most of these ...