Gözde Yildiz

The paper uses machine learning and multi-omic data to analyze recombination patterns in the A and C subgenomes of Brassica napus, finding distinct landscape features between them.

The paper identifies and characterizes super-enhancers in Brassica napus, revealing their asymmetrical distribution and functional impact on gene expression and regulatory processes.

This study uses pangenome graphs to analyze structural variants in Brassica napus, showing they impact gene expression and eQTL analysis better than single references.

This study benchmarks SV detection tools using Oxford Nanopore reads in crop plants, evaluating performance across different coverages and species.