Identifying potential targets in endothelial to mesenchymal transition-mediated atherosclerosis using bioinformatics and machine learning
- DOI
- 10.7717/peerj.21863
- Published
- 2026-11-03
- Container
- PeerJ
- Publisher
- PeerJ
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.7717/peerj.21863,
title = {Identifying potential targets in endothelial to mesenchymal transition-mediated atherosclerosis using bioinformatics and machine learning},
author = {Zhengjun Hou and Sihan Chen and Yuliang Cui and Qinfeng Ma and Jiandong Chen and Kunxian Shu},
year = {2026},
journal = {PeerJ},
doi = {10.7717/peerj.21863},
url = {https://doi.org/10.7717/peerj.21863}
}RIS
TY - JOUR TI - Identifying potential targets in endothelial to mesenchymal transition-mediated atherosclerosis using bioinformatics and machine learning AU - Zhengjun Hou AU - Sihan Chen AU - Yuliang Cui AU - Qinfeng Ma AU - Jiandong Chen AU - Kunxian Shu PY - 2026 JO - PeerJ DO - 10.7717/peerj.21863 UR - https://doi.org/10.7717/peerj.21863 ER -
APA
Hou, Z., Chen, S., Cui, Y., Ma, Q., Chen, J., & Shu, K. (2026). Identifying potential targets in endothelial to mesenchymal transition-mediated atherosclerosis using bioinformatics and machine learning. PeerJ. https://doi.org/10.7717/peerj.21863
Source records
- crossref · retrieved 2026-11-09T18:35:14.707Z