G. A. Henry

Predicting fitness related traits using gene expression and machine learning

This study uses machine learning to analyze gene expression data from Ipomoea hederacea, finding that photosynthesis and stress-related genes are under selection and important for predicting fitness.

Strong selection is poorly aligned with genetic variation in Ipomoea hederacea: implications for divergence and constraint

The study examines selection and genetic variation in Ipomoea hederacea, finding poor alignment between selection and genetic covariance structure and divergence patterns.

G-matrix stability of clinally diverging populations of an annual weed.

The paper examines genetic (co)variances of clinally varying traits in Ipomoea hederacea populations to assess how genetic architecture influences divergence across its range.