一种鰤鱼诺卡氏菌株的毒力等级评估方法及系统
By constructing a dedicated virulence gene feature library and a random forest regression model for Nocardia amberjack, combined with semi-supervised learning, the problems of long cycle and high cost in virulence assessment of Nocardia amberjack were solved, and rapid and accurate virulence level assessment was achieved, providing a basis for the screening of vaccine candidate strains.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGXI ACADEMY OF FISHERY SCI
- Filing Date
- 2026-05-22
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for assessing the virulence of Nocardia amberjack are time-consuming, costly, and difficult to standardize. Traditional high-throughput sequencing cannot quantify virulence levels, and machine learning methods lack specific virulence characteristics and continuous virulence assessment schemes for Nocardia.
A classified and weighted exclusive virulence gene feature library of Nocardia amberjack was constructed. By combining the random forest regression algorithm and a semi-supervised learning framework, LD50 prediction and virulence level assessment were achieved through whole genome sequence analysis.
This method enables rapid and accurate assessment of the virulence level of Nocardia amberjack, reducing experimental costs and time, and providing a basis for decision-making in the screening of vaccine candidate strains.
Smart Images
Figure CN122245453B_ABST