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L(2,1)-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions
BACKGROUND: Predicting drug-target interactions is time-consuming and expensive. It is important to present the accuracy of the calculation method. There are many algorithms to predict global interactions, some of which use drug-target networks for prediction (ie, a bipartite graph of bound drug pai...
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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2019
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6557743/ https://ncbi.nlm.nih.gov/pubmed/31182006 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-2768-7 |
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