September 10, 2025

Predicting FOX Genes and Design of a Minimal FOX Gene Complement with a Data-Centric Machine Learning Approach

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Machine learning predicts novel fox genes in diazotrophic cyanobacteria, suggesting significant roles in nitrogen fixation.

Predictions reveal novel fox gene candidates conserved in diazotrophs while absent in non-diazotrophic cyanobacteria.
Machine learning achieved a predictive performance of up to 0.83 ROC-AUC using features from multi-omic data.
Comparative bioinformatics across 12 unique cyanobacterial proteomes confirmed the relevance of these predictions for nitrogen fixation.
Developed a minimal fox genome optimizer tool that aids in the rational design of nitrogen fixation capabilities for crops.

Young et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark