Predicting Potential Drug Targets Using Tensor Factorisation and Knowledge Graph Embeddings
Cheng Ye,
Rowan Swiers,
Stephen Bonner
et al.
Abstract:The drug discovery and development process is a long and expensive one, costing over 1 billion USD on average per drug and taking 10-15 years. To reduce the high levels of attrition throughout the process, there has been a growing interest in applying machine learning methodologies to various stages of drug discovery process in the recent decade, including at the earliest stage -identification of druggable disease genes. In this paper, we have developed a new tensor factorisation model to predict potential dru… Show more
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