Integrated transcriptome analysis and machine learning to construct a homeostatic model of acetylation for bladder cancer and validate the key gene CES1.
- DOI
- 10.21037/tau-2026-0435
- Published
- 2026 Aug 31
- Container
- Translational andrology and urology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.21037/tau-2026-0435,
title = {Integrated transcriptome analysis and machine learning to construct a homeostatic model of acetylation for bladder cancer and validate the key gene CES1.},
author = {Cao J and Yang J and Shang W and Tan H and Zhou Q and Jia B and Guo J},
year = {2026},
journal = {Translational andrology and urology},
doi = {10.21037/tau-2026-0435},
url = {https://doi.org/10.21037/tau-2026-0435}
}RIS
TY - JOUR TI - Integrated transcriptome analysis and machine learning to construct a homeostatic model of acetylation for bladder cancer and validate the key gene CES1. AU - Cao J AU - Yang J AU - Shang W AU - Tan H AU - Zhou Q AU - Jia B AU - Guo J PY - 2026 JO - Translational andrology and urology DO - 10.21037/tau-2026-0435 UR - https://doi.org/10.21037/tau-2026-0435 ER -
APA
J, C., J, Y., W, S., H, T., Q, Z., B, J., & J, G. (2026). Integrated transcriptome analysis and machine learning to construct a homeostatic model of acetylation for bladder cancer and validate the key gene CES1.. Translational andrology and urology. https://doi.org/10.21037/tau-2026-0435
Source records
- pubmed · retrieved 2026-09-25T13:52:45.357Z