Recently, a research team from the Computer Network Information Center of the Chinese Academy of Sciences has developed AuraGenome, an intelligent generation framework for circular genome visualization powered by large models. AuraGenome breaks away from the traditional “manual-script-static” paradigm and introduces a novel “natural language-agent-interactive” approach, enabling rapid transformation of genomic data into high-quality, interactive visualizations. The system supports full-process traceability and reusability, significantly enhancing reproducibility and efficiency in genomic analysis. In a study on chromosomal translocations in acute myeloid leukemia, researchers generated comprehensive visualizations of structural variations and transcriptional activity within just 20 minutes, successfully identifying and interactively marking potential biomarker regions. In another experiment, the team reproduced the classic interactive mutation landscape of melanoma in only seven minutes with high fidelity, matching the results published in a seminal paper. Comprehensive benchmarking demonstrated that AuraGenome outperforms conventional tools like Circos—achieving a 69% improvement in efficiency and increasing accuracy to 89%. This advancement marks a pivotal shift: scientists can now focus on biological insights rather than mastering complex visualization tools. The research was published in IEEE Computer Graphics and Applications. The work was supported by the Chinese Academy of Sciences’ Strategic Priority Research Program (Category A). This breakthrough represents a significant step forward in intelligent visual analytics for genomics, establishing a new standard for the automated, intelligent, and interactive generation of circular genome visualizations.