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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, ...
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
(Bmc, 2019)
Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the ...
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 ...
Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants
(Wiley, 2018)
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and ...
CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations
(Oxford Academic, 2021)
Systemic analysis of available large-scale biological/biomedical data is critical for studying biological mechanisms, and developing novel and effective treatment approaches against diseases. However, different layers of ...
Transfer learning for drug–target interaction prediction
(Oxford University Press, 2023)
MotivationUtilizing AI-driven approaches for drug-target interaction (DTI) prediction require large volumes of training data which are not available for the majority of target proteins. In this study, we investigate the ...