Multi-modal transcriptomics: integrating machine learning and convolutional neural networks to identify immune biomarkers in atherosclerosis
This study introduces three signature genes for atherosclerosis, shaping a novel paradigm for investigating clinical immunological medications. It distinguishes the high biocidal C2 subtype from the inflammation-modulating C1 subtype, utilizing identified signature gene as crucial targets.
Authors
- Juyi Wan (ORCID: https://orcid.org/0000-0003-1314-1673)
- Qingwen Hu
- Hao Chi (ORCID: https://orcid.org/0000-0002-5210-0770)
- Bin Yih Liao (ORCID: https://orcid.org/0000-0003-4636-4339)
- Wei Fan (ORCID: https://orcid.org/0000-0001-5036-8733)
- Cheng‐Lu Jiang (ORCID: https://orcid.org/0000-0002-2130-7760)
- Yemeng Chen (ORCID: https://orcid.org/0000-0001-7746-6253)
- Jinbang Huang
- Jieying Zhang (ORCID: https://orcid.org/0000-0002-3967-9220)
- Lai Jiang (ORCID: https://orcid.org/0000-0002-4639-8136)
- Haotian Lai
- Haiqing Chen (ORCID: https://orcid.org/0009-0009-4555-9362)
- Shengke Zhang
- Guanhu Yang
- Xiuben Yan
Institutions
- Tianjin University of Traditional Chinese Medicine (CN)
- Southwest Medical University (CN)
- Ohio University (US)
- First Teaching Hospital of Tianjin University of Traditional Chinese Medicine (CN)
- New York College of Traditional Chinese Medicine (US)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2024-11-26
- DOI
- https://doi.org/10.3389/fcvm.2024.1397407
- Citations
- 5
- Primary Topic
- Atherosclerosis and Cardiovascular Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.20