A. Shami

Integrative targeted blood gene-expression profiling, coding-region genetic variants, and machine learning identify candidate biomarkers of milk fever in Holstein dairy cattle

The results show that the combination of targeted blood gene-expression profiling, functional genetic variation, and machine-learning methods offers a powerful framework for genomic prediction, precision livestock management, and future marker-assisted breeding strategies.

Genetic dissection of inherited cold-stress reveals resilience hotspots in barley

Integrated genome-wide and expression analysis of YABBY genes in Triticum aestivum under PEG-induced osmotic, cold and combined stress.

This revised study re-examined YABBY-associated protein models and integrated phylogenetic, structural, promoter, public transcriptomic and qRT-PCR analyses, with emphasis on cold and PEG-induced osmotic stress, and prioritizes candidates for future functional validation under controlled osmotic and cold stress conditi...