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. 2025 May 13;15(10):1407. doi: 10.3390/ani15101407

Figure 5.

Figure 5

Identification of hypoxia-related genes using Lasso regression and Random Forest. (A) Optimization of Lasso regression parameters for hypoxia-related gene selection; (B) Random Forest-based ranking of key genes contributing to hypoxia adaptation, as determined by mean decrease in Gini scores. (C) The top 20 candidate genes identified by Random Forest in the environmental stress gene set. (D) The top 20 candidate genes identified by Random Forest in the genetic adaptation gene set. (E) The overlapping genes identified by both machine learning methods among the environmental stress genes were MAP3K5, TGFBR2 and ITGB5. (F) The overlapping genes identified by both machine learning methods among the genetic adaptation genes were RSPO1, TGFBR2, and ITGB5.