Summary of Hgtdr: Advancing Drug Repurposing with Heterogeneous Graph Transformers, by Ali Gharizadeh et al.
HGTDR: Advancing Drug Repurposing with Heterogeneous Graph Transformers
by Ali Gharizadeh, Karim Abbasi, Amin Ghareyazi, Mohammad R.K. Mofrad, Hamid R. Rabiee
First submitted to arxiv on: 12 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Quantitative Methods (q-bio.QM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This abstract proposes a novel approach to drug repurposing called HGTDR (Heterogeneous Graph Transformer for Drug Repurposing), which addresses the limitations of current methods. The authors recognize that existing approaches have limited scope, lack end-to-end functionality, and require manual implementation and expert knowledge. They claim their method can handle heterogeneous data, extract information from diverse entities, and provide desired output. In a comparative evaluation, HGTDR performs similarly to previous methods. Furthermore, the authors validate their top ten drug repurposing suggestions through medical studies, which have shown promising results. Additionally, they demonstrate HGTDR’s capability to predict other types of relations, such as drug-protein and disease-protein interactions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Drug repurposing is a way to reuse existing drugs for new diseases, saving time and money in the process. The current methods used for this are limited and require experts to implement them manually. Researchers propose a new approach called HGTDR that can handle different types of data and provide desired results. They tested their method with previous approaches and showed similar performance. Additionally, they validated some of their suggestions by studying medical records. |
Keywords
» Artificial intelligence » Transformer
