Published September 7, 2019
| Version v1
Dataset
Open
Integrated knowledge graphs and embeddings vectors for drug-drug interaction prediction
Contributors
Project member:
Researcher (3):
Supervisor:
- 1. Fraunhofer FIT, Germany
- 2. University of Dhaka, Bangladesh
- 3. RWTH Aachen University, Germany
Description
The associated Knowledge Graphs for predicting potential drug-drug interaction, which is used in our paper titled "Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network". Please consider citing the following paper if you plan or used our datasets.
Md. Rezaul Karim, Michael Cochez, Joao Bosco Jares, Mamtaz Uddin, Oya Beyan, and Stefan Decker, "Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network", In 10th ACM Int’l Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB ’19), September 7–10, 2019, Niagara Falls, NY, USA.
Notes
Please refer to https://github.com/rezacsedu/DDI-prediction-KG-embeddings-Conv-LSTM and contact rezaul.karim@rwth-aachen.de for the graph embeddings and other computational materials.
Files
CrossE_Drug_Embeddedings.txt
Files
(611.6 MB)
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md5:d72cd01d7ee94676c2994dd79db38b9e
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md5:b0591304c2a19787b5131ae391ddb56e
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257.7 MB | Download |
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md5:b0591304c2a19787b5131ae391ddb56e
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257.7 MB | Download |
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md5:0d1478cdf298c26a33e875e54ec78d58
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md5:9b65dbe77510addb3e6d7464286752b5
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Additional details
Related works
- Is supplement to
- 10.1145/3307339.3342161 (DOI)
References
- Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, Assempour N, Iynkkaran I, Liu Y, Maciejewski A, Gale N, Wilson A, Chin L, Cummings R, Le D, Pon A, Knox C, Wilson M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2017 Nov 8. doi: 10.1093/nar/gkx1037.
- Law V, Knox C, Djoumbou Y, Jewison T, Guo AC, Liu Y, Maciejewski A, Arndt D, Wilson M, Neveu V, Tang A, Gabriel G, Ly C, Adamjee S, Dame ZT, Han B, Zhou Y, Wishart DS. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 2014 Jan 1;42(1):D1091-7.
- Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS. DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res. 2011 Jan;39(Database issue):D1035-41.
- Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, Gautam B, Hassanali M. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res. 2008 Jan;36(Database issue):D901-6.
- Kanehisa, Minoru, et al. "KEGG for representation and analysis of molecular networks involving diseases and drugs." Nucleic acids research 38.suppl_1 (2009): D355-D360.
- M. Whirl-Carrillo, E.M. McDonagh, J. M. Hebert, L. Gong, K. Sangkuhl, C.F. Thorn, R.B. Altman and T.E. Klein. "Pharmacogenomics Knowledge for Personalized Medicine" Clinical Pharmacology & Therapeutics (2012) 92(4): 414-417.
- Tatonetti, Nicholas P., et al. "Data-driven prediction of drug effects and interactions." Science translational medicine 4.125 (2012): 125ra31-125ra31.
- Wishart DS, Feunang YD, Guo AC, Lo EJ, Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, Assempour N, Iynkkaran I, Liu Y, Maciejewski A, Gale N, Wilson A, Chin L, Cummings R, Le D, Pon A, Knox C, Wilson M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2017 Nov 8. doi: 10.1093/nar/gkx1037.