3 Result(s)
within
Chapter
Conference Paper
**ao-Rui Su
Machine Learning
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Chapter and Conference Paper
MRLDTI: A Meta-path-Based Representation Learning Model for Drug-Target Interaction Prediction
Predicting the relationships between drugs and targets is a crucial step in the course of drug discovery and development. Computational prediction of associations between drugs and targets greatly enhances the...
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Chapter and Conference Paper
A Unified Deep Biological Sequence Representation Learning with Pretrained Encoder-Decoder Model
Machine learning methods are increasingly being applied to model and predict biomolecular interactions, while efficient feature representation plays a vital role. To this end, a unified biological sequence dee...
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Chapter and Conference Paper
A Novel Computational Approach for Predicting Drug-Target Interactions via Network Representation Learning
Detection of drug-target interactions (DTIs) has a beneficial effect on both pathogenesis and drugs discovery. Although a huge number of DTIs have been generated recently, the number of known interactions is s...
