Identification of diagnostic biomarkers for neonatal necrotizing enterocolitis via machine learning screening and single‐cell virtual gene knockout validation
Xue Liu, Wenqiang Sun, Zengxue Hu, Yihui Li, Jingtao Bian, Xueping Zhu · 2026
Read Identification of diagnostic biomarkers for neonatal necrotizing enterocolitis via machine learning screening and single‐cell virtual gene knockout validation by Xue Liu, Wenqiang Sun, Zengxue Hu, Yihui Li, Jingtao Bian, Xueping Zhu (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-13240151.txt.
Description
Xue Liu and colleagues hunt early warning genes for a devastating newborn gut disease in a 2026 computational study. Necrotizing enterocolitis strikes premature babies and kills a fifth to a third of cases, partly because no clear early blood or tissue marker exists to trigger fast treatment.
The team merged five public gene datasets and ran more than a hundred machine learning combinations to find a diagnostic signature. Three genes stood out, one falling and two rising in diseased tissue, with the best model separating cases almost perfectly. Single-cell data, virtual gene knockouts in a computer model, and mouse experiments all backed the trio. Immune cell mixes also shifted in characteristic ways.
Catalog record
| CREATOR | Xue Liu, Wenqiang Sun, Zengxue Hu, Yihui Li, Jingtao Bian, Xueping Zhu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |