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A multitask transfer learning framework for the prediction of virus-human protein-protein interactions
We developed a multitask transfer learning approach that exploits the information of around 24 million protein sequences and the interaction patterns from the human interactome to counter the problem of small training datasets.
MuCoMiD: A Multitask Convolutional Learning Framework for miRNA-Disease Association Prediction
To effectively test the generalization capability of our model, we construct large-scale experiments on standard benchmark datasets as well as our proposed larger independent test sets and case studies.
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