Xun Gu

The paper investigates the relationship between gene pleiotropy and evolutionary rates, finding positive correlations between effective pleiotropy and various molecular features.

This paper examines how macro-perturbation barriers affect molecular evolution, showing that neutral mutants evolve slower than mutation rates due to these barriers, and applies this to polyploidization.

MATTE identifies differentially expressed genes and modules in noisy transcriptome data, improving analysis of phenotype-related biological insights.