Integrative Multi-Omics Analysis with Interpretable Machine Learning Prioritizes Candidate Biomarkers for Bladder Cancer
- DOI
- 10.2174/0115665232538656261006070001
- Published
- 2026-10-27
- Container
- Current Gene Therapy
- Publisher
- Bentham Science Publishers Ltd.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2174/0115665232538656261006070001,
title = {Integrative Multi-Omics Analysis with Interpretable Machine Learning Prioritizes Candidate Biomarkers for Bladder Cancer},
author = {Huihong Guan and Xinyu Liu and Ting Hong and Hao Li and Guoyuan Liu and Yonghai Zhang and Xuwei Hong},
year = {2026},
journal = {Current Gene Therapy},
doi = {10.2174/0115665232538656261006070001},
url = {https://doi.org/10.2174/0115665232538656261006070001}
}RIS
TY - JOUR TI - Integrative Multi-Omics Analysis with Interpretable Machine Learning Prioritizes Candidate Biomarkers for Bladder Cancer AU - Huihong Guan AU - Xinyu Liu AU - Ting Hong AU - Hao Li AU - Guoyuan Liu AU - Yonghai Zhang AU - Xuwei Hong PY - 2026 JO - Current Gene Therapy DO - 10.2174/0115665232538656261006070001 UR - https://doi.org/10.2174/0115665232538656261006070001 ER -
APA
Guan, H., Liu, X., Hong, T., Li, H., Liu, G., Zhang, Y., & Hong, X. (2026). Integrative Multi-Omics Analysis with Interpretable Machine Learning Prioritizes Candidate Biomarkers for Bladder Cancer. Current Gene Therapy. https://doi.org/10.2174/0115665232538656261006070001
Source records
- crossref · retrieved 2026-11-10T15:11:47.965Z