Zitong Li

The paper identifies environmental factors and growth stages affecting fibre yield and quality in rain-grown cotton using statistical models and field data.

This paper develops a GEI-based genomic prediction method for cotton traits using dimensionality reduction and Bayesian models, showing better performance than deep learning approaches.

This paper improves genomic prediction accuracy for cotton fibre traits by integrating gene-network clusters derived from RNA-seq data into Bayesian models.

This study identifies conserved RNA-binding motifs in coronavirus nucleocapsid proteins that enable broad-spectrum antiviral drug development.

The paper identifies 51 significant SNPs from 39 candidate genes associated with wood formation traits in Norway spruce using genome-wide association mapping.

The paper identifies QTL associated with adaptive traits in Scots pine using a three-generation pedigree, finding 62 significant QTL with variance explained up to 18.9%.