Integrative bioinformatics and machine learning approach unveils potential biomarkers linking coronary atherosclerosis and fatty acid metabolism-associated gene
Abstract Background Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts as a major contributor to cardiovascular diseases. Advancements in lipidomics and metabolomics have unveiled the complex role of fatty acid me...
Saved in:
Main Authors: | Hong Li, Yongyun Xu, Aiting Wang, Chuanxin Zhao, Man Zheng, Chunyan Xiang |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-01-01
|
Series: | Journal of Cardiothoracic Surgery |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13019-024-03199-4 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes
by: Fanqi Liang, et al.
Published: (2025-01-01) -
Screening key genes for intracranial aneurysm rupture using LASSO regression and the SVM-RFE algorithm
by: Qi Wu, et al.
Published: (2025-01-01) -
Two-centers machine learning analysis for predicting acid-fast bacilli results in tuberculosis sputum tests
by: Jichong Zhu, et al.
Published: (2025-02-01) -
Synthesis, In vitro antimicrobial activity, and In silico bioinformatical approach of xanthone-fatty acid esters against Staphylococcus aureus, Escherichia coli, and Candida albicans
by: Yehezkiel Steven Kurniawan, et al.
Published: (2025-04-01) -
DC serial arc fault recognition in aircraft using machine learning techniques
by: Raul Carreira Rufato, et al.
Published: (2025-03-01)