Predicting circRNA-Drug Sensitivity Using Integrated Hybrid Graph and Molecular Features.
- DOI
- 10.1007/s12539-026-00870-3
- Published
- 2026 Aug 26
- Container
- Interdisciplinary sciences, computational life sciences
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1007/s12539-026-00870-3,
title = {Predicting circRNA-Drug Sensitivity Using Integrated Hybrid Graph and Molecular Features.},
author = {Wang Y and Shen W and Li J and Hu J and Peng J and You Z and Shang X},
year = {2026},
journal = {Interdisciplinary sciences, computational life sciences},
doi = {10.1007/s12539-026-00870-3},
url = {https://doi.org/10.1007/s12539-026-00870-3}
}RIS
TY - JOUR TI - Predicting circRNA-Drug Sensitivity Using Integrated Hybrid Graph and Molecular Features. AU - Wang Y AU - Shen W AU - Li J AU - Hu J AU - Peng J AU - You Z AU - Shang X PY - 2026 JO - Interdisciplinary sciences, computational life sciences DO - 10.1007/s12539-026-00870-3 UR - https://doi.org/10.1007/s12539-026-00870-3 ER -
APA
Y, W., W, S., J, L., J, H., J, P., Z, Y., & X, S. (2026). Predicting circRNA-Drug Sensitivity Using Integrated Hybrid Graph and Molecular Features.. Interdisciplinary sciences, computational life sciences. https://doi.org/10.1007/s12539-026-00870-3
Source records
- pubmed · retrieved 2026-09-25T06:45:57.266Z