Exploration of candidate genes associated with rare SNVs in pulmonary stenosis using whole-exome sequencing and machine learning
Yuting Liu, Sun Chen, Yongzhou Liang, Suqiu Huang, Bingyao Zhang, Shuqi Liu, Ling Yang, Liqing Zhao, Rang Xu, Yurong Wu · 2026
Read Exploration of candidate genes associated with rare SNVs in pulmonary stenosis using whole-exome sequencing and machine learning by Yuting Liu, Sun Chen, Yongzhou Liang, Suqiu Huang, Bingyao Zhang, Shuqi Liu, Ling Yang, Liqing Zhao, Rang Xu, Yurong Wu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13278683.txt.
Description
Yuting Liu and colleagues combine gene sequencing with machine learning to find candidate genes for pulmonary stenosis, in a 2026 study. The condition narrows the heart's pulmonary valve and can threaten life when severe. Its genetic roots involve many genes and remain only partly mapped.
Whole-exome data from 185 patients and one hundred controls were filtered for rare harmful variants. Statistical burden tests were run beside three machine learning methods to rank genes. Random forest agreed most closely with the burden results. Seventeen candidate genes survived the combined screen, including several known in heart development. Lab checks confirmed the candidates are active in human pulmonary artery cells.
Catalog record
| CREATOR | Yuting Liu, Sun Chen, Yongzhou Liang, Suqiu Huang, Bingyao Zhang, Shuqi Liu, Ling Yang, Liqing Zhao, Rang Xu, Yurong Wu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 43 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |