基于药物和疾病特征关联的药物重定位混合推荐算法

he algorithm of drug repositioning based on collaborative filtering was studied. Considering the great influence of data sparsity on collaborative filtering algorithm, this paper proposed a hybrid recommendation algorithm based on the association of drug and disease characteristics. The algorithm not only used the data of drug and disease, but also used the information of drug structure, target protein, side effect and drug-disease feature matrix to calculate the similarity between drugs, which reduced the influence of data sparsity to the recommendation effect and improves the precision of recommendation. The results of contrastive experiment showed that the algorithm has a good recommendation effect, and can explore the drug-disease combinations which have potential relationship, and further verified that the algorithm can be effectively applied to drug repositioning.