Human essential gene identification based on feature fusion and feature screening
Zhao‐Yue Zhang, Yue‐Er Fan, Cheng‐Bing Huang, Meng‐Ze Du · 2024
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Description
Zhao-Yue Zhang and three co-authors build a tool to spot essential human genes in a 2024 paper. Essential genes keep a cell alive when food is ample, and they tempt drug makers as targets. But which genes count as essential shifts with conditions, so lab tests alone cannot settle the list.
The team took gene lists from human cancer cell lines and encoded each gene's sequence seven ways. They then fused the encodings, screened out the weak parts, and trained learning models on what remained. Single-encoding models already scored well. After fusion and screening, classic models improved and a deep learning model scored best of all. The authors offer the pipeline as a sharper way to nominate essential genes.
Catalog record
| CREATOR | Zhao‐Yue Zhang, Yue‐Er Fan, Cheng‐Bing Huang, Meng‐Ze Du |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 22 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |