Sorghum Pangenome Graph for kmer-based Association Study using Machine-Learning

My PhD project focuses on building a pangenome graph for sorghum (Sorghum bicolor) using the latest high-quality, chromosome-scale assemblies. This graph-based representation will help reveal genetic variants that are often missed in single-reference approaches, offering new insights into the population structure and agronomically important traits of sorghum. By integrating this pangenome with big-data-related methods like kmer-based association studies and machine learning, the project aims to identify causal loci linked to key traits, ultimately supporting more informed and efficient breeding strategies.