Literature DB >> 29917050

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

Rawan S Olayan, Haitham Ashoor, Vladimir B Bajic.   

Abstract

Year:  2018        PMID: 29917050      PMCID: PMC6198857          DOI: 10.1093/bioinformatics/bty417

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


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Bioinformatics Volume 34, Issue 7, 24 November 2017, Pages 1164–1173, https://doi.org/10.1093/bioinformatics/btx731 In our study (Olayan ), we performed 96 computational experiments, including six that are related to the COSINE method (Lim ). 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 analysis 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. Click here for additional data file.
  2 in total

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

Authors:  Rawan S Olayan; Haitham Ashoor; Vladimir B Bajic
Journal:  Bioinformatics       Date:  2018-04-01       Impact factor: 6.937

2.  Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.

Authors:  Hansaim Lim; Paul Gray; Lei Xie; Aleksandar Poleksic
Journal:  Sci Rep       Date:  2016-12-13       Impact factor: 4.379

  2 in total
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Journal:  Chin Med       Date:  2020-08-26       Impact factor: 5.455

Review 2.  A brief review of protein-ligand interaction prediction.

Authors:  Lingling Zhao; Yan Zhu; Junjie Wang; Naifeng Wen; Chunyu Wang; Liang Cheng
Journal:  Comput Struct Biotechnol J       Date:  2022-06-03       Impact factor: 6.155

3.  Dipeptide Frequency of Word Frequency and Graph Convolutional Networks for DTA Prediction.

Authors:  Xianfang Wang; Yifeng Liu; Fan Lu; Hongfei Li; Peng Gao; Dongqing Wei
Journal:  Front Bioeng Biotechnol       Date:  2020-04-03

4.  Prediction of Drug-Target Interaction Using Dual-Network Integrated Logistic Matrix Factorization and Knowledge Graph Embedding.

Authors:  Jiaxin Li; Xixin Yang; Yuanlin Guan; Zhenkuan Pan
Journal:  Molecules       Date:  2022-08-12       Impact factor: 4.927

  4 in total

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