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DDR: efficient computational method to predict drug–target interactions using graph mining and machine learning approaches

Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic
2018 Bioinformatics  

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In our study (Olayan et al., 2018) , we performed 96 computational experiments, including six that are related to the COSINE method (Lim et al., 2016) . Re-evaluating all numerical results we reported, we found that out of the six tests (5 cross-validation tests and 1 hold-out test) we performed for the COSINE method, the performance of COSINE in two of these tests, both related to the DrugBank_FDA dataset, should be corrected. This implied a few corrections in the article. The repeated
more » ... confirms that the original qualitative conclusions regarding the newly introduced DDR method stands unaltered. All necessary changes are implemented in the article and associated Supplementary material. The article has also now been updated online.
doi:10.1093/bioinformatics/bty417 pmid:29917050 fatcat:3hnn6d3juvfwlkz4nn3bttzbla
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Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic. "DDR: efficient computational method to predict drug–target interactions using graph mining and machine learning approaches." Bioinformatics 34.21 (2018)