Genome Understanding

Genome understanding aims to decipher the complex relationships between genomic information and biological function, ultimately facilitating advancements in medicine and biotechnology. Current research heavily utilizes machine learning, including large language models and graph neural networks, to analyze diverse genomic data types (e.g., RNA-seq, protein-protein interaction networks) and predict gene function, essentiality, and disease associations. These computational approaches are improving the efficiency and accuracy of gene discovery, enabling more effective drug design and personalized medicine strategies. Furthermore, explainable AI methods are being developed to enhance the transparency and interpretability of these powerful predictive models.