Abstract: The rapid growth of genomic data has opened unprecedented opportunities to understand biology at the scale of entire chromosomes. However, analyzing and interpreting such large, complex datasets requires advanced computational methods that can integrate diverse sources of information and provide biologically meaningful insights.
In this talk, Dr. G.P.S. Raghava and Dr. Shilpa Garg from the University of Copenhagen will present cutting-edge computational approaches for chromosome-scale genomics. The discussion will explore how machine learning, statistical modeling, and algorithmic innovations are being applied to decode structural variations, gene regulation, and evolutionary patterns across chromosomes.
Key themes include:
Development of scalable algorithms for handling massive genomic datasets.
Integration of multi-omics data to uncover functional relationships at the chromosome level.
Applications of AI and computational biology in precision medicine and population genomics.
Challenges in ensuring accuracy, reproducibility, and interpretability of computational genomic analyses.
By bridging computational innovation with biological discovery, the speakers will highlight how these approaches are transforming our ability to study genomes at unprecedented resolution. The presentation will emphasize the potential of chromosome-scale genomics to advance personalized healthcare, evolutionary biology, and our broader understanding of life’s complexity.