Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach
Publication
, Conference
Dhami, DS; Yan, S; Kunapuli, G; Page, D; Natarajan, S
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2021
Most approaches for predicting drug-drug interactions (DDIs) have focused on text. We present the first work that uses multiple drug structure data - images, string representations and relationship representations. We exploit the recent advances in deep networks to integrate these varied sources of inputs in predicting DDIs. Our empirical evaluations clearly demonstrate the efficacy of combining heterogeneous data in predicting DDIs.
Duke Scholars
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
January 1, 2021
Volume
12721 LNAI
Start / End Page
252 / 257
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Dhami, D. S., Yan, S., Kunapuli, G., Page, D., & Natarajan, S. (2021). Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12721 LNAI, pp. 252–257). https://doi.org/10.1007/978-3-030-77211-6_28
Dhami, D. S., S. Yan, G. Kunapuli, D. Page, and S. Natarajan. “Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12721 LNAI:252–57, 2021. https://doi.org/10.1007/978-3-030-77211-6_28.
Dhami DS, Yan S, Kunapuli G, Page D, Natarajan S. Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. p. 252–7.
Dhami, D. S., et al. “Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12721 LNAI, 2021, pp. 252–57. Scopus, doi:10.1007/978-3-030-77211-6_28.
Dhami DS, Yan S, Kunapuli G, Page D, Natarajan S. Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. p. 252–257.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
Publication Date
January 1, 2021
Volume
12721 LNAI
Start / End Page
252 / 257
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences