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What is Predicting Microbe-Drug-Disease Relationships about?
This review summarizes computational methods for predicting relationships between human microbes, drugs, and diseases. It introduces 17 datasets relevant to identifying these relationships and groups representative computational models into five categories: network, matrix factorization, matrix completion, regularization, and artificial neural networks. The review provides an in-depth analysis of predictive methods within each category and compares their frameworks. It also discusses challenges and opportun
- Author
- han zhou
- Language
- EN