Xinjun Zhang

The paper uses Neanderthal ancestry patterns to identify genomic regions enriched with recessive deleterious mutations using a machine learning classifier.

The paper tracks genome-wide evolutionary dynamics in hybrid Drosophila populations, showing rapid purging of minority ancestry and repeated retention of selected regions through adaptive introgression.

TRACER predicts terpene skeletal rearrangements by learning enzyme-product associations, identifying novel carbon skeletons and mechanistic insights.

The paper develops DEEP, an ARG-free method to detect Denisovan-mediated superarchaic introgression, finding 0.4-0.6% of genomic windows with evidence of such ancestry in Oceanians, Tibetans, and Han Chinese.

This study evaluates how admixture, selection, and demographic history influence GWAS power and fine-mapping precision in admixed populations using simulations and empirical data.

This paper examines how scaling affects coalescent and forward simulations in human and Drosophila populations, finding that scaling impacts diversity estimates, runtime, and selection effects differently in each species.