Deep learning of multimodal networks with topological regularization for drug repositioning
STRGNN demonstrates superior accuracy compared to existing methods and has identified several novel drug effects, corroborating existing literature. STRGNN emerges as a powerful tool for drug prediction and discovery. The source code for STRGNN, along with the dataset for performance evaluation, is available at https://github.com/yuto-ohnuki/STRGNN.git .
Authors
- Manato Akiyama (ORCID: https://orcid.org/0000-0002-5177-3199)
- Yuto Ohnuki
- Yasubumi Sakakibara
Institutions
- Keio University (JP)
Publication Details
- Journal
- Journal of Cheminformatics
- Published
- 2024-08-23
- DOI
- https://doi.org/10.1186/s13321-024-00897-y
- Citations
- 11
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 3.98
Funders
- Ministry of Education, Culture, Sports, Science and Technology