Computational Drug-target Interaction Prediction based on Graph Embedding and Graph Mining-Reference-Cited by-同舟云学术

Computational Drug-target Interaction Prediction based on Graph Embedding and Graph Mining

Published:2020-01-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics
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Author:

Thafar Maha A.¹,Albaradie Somayah²,Olayan Rawan S.³,Ashoor Haitham³,Essack Magbubah³,Bajic Vladimir B.³

Affiliation:

1. King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia Taif University, College of Computers and Information Technology, Taif, Saudi Arabia

2. King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia King Abdulaziz University, Faculty of Computing and Information Technology, Jeddah, Saudi Arabia

3. King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center (CBRC), Thuwal, Saudi Arabia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3386052.3386062

Reference47 articles.

1. The cost of drug development: A systematic review

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

3. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

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