Artificial intelligence has identified more than 160,000 new types of RNA viruses, dramatically expanding our understanding of viral diversity. This is driven by artificial intelligence Discovery methodDeveloped by an international research team, it analyzes genetic “dark matter” to detect viruses in extreme environments, potentially revolutionizing virology and bioinformatics.
The revolutionary discovery of more than 160,000 new types of RNA viruses comes from a team led by Alibaba Cloud, Sun Yat-sen University and the University of Sydney. The team developed a deep learning algorithm, LucaProt, that set a new standard in virology by integrating advanced AI technology with traditional methods. This important progress is being led by experts such as Professor Edward Holmes from the University of Sydney and Professor Mang Shi from Sun Yat-sen University, With contributions From Dr. Zhao Rongli from Alibaba Cloud Intelligence.
How AI is transforming viral discoveries
LucaProt, specifically designed to detect RNA viruses, uses a deep learning model that outperforms traditional bioinformatics pipelines. By examining the genetic sequences and secondary structures of replication proteins, this AI tool can quickly and accurately identify virus types, at a rate of approximately one per second. This capability provides a dynamic approach to virus detection, significantly reducing the time traditionally required for such research.
Revealing the hidden world of RNA viruses
Research published in Cell magazineIt is the largest virus discovery study ever conducted. Viruses have been discovered in diverse and extreme environments, such as the atmosphere, hot springs, and hydrothermal vents. These results not only demonstrate the remarkable biodiversity of RNA viruses, but also highlight their resilience and adaptability in extreme environments. This has opened new horizons for understanding how viruses and other basic life forms evolve and exist in such environments.
Implications for medicine, health technology and beyond
This discovery has potential applications in medicine, health technology, and agricultural technology. Researchers can better predict and control future viral pandemics by improving our understanding of viral biodiversity. In addition, the AI-based methods developed in this research could pave the way for new tools in microbial genomics and epidemiology, allowing for more accurate and faster responses to viral threats.
With this achievement, the researchers aim to improve and expand the capabilities of their AI tool, with the hope of uncovering more viral diversity in the future. The integration of AI into virology promises not only to accelerate discoveries but also to provide insight into unknown aspects of viral evolution and ecology, representing a major leap forward for the field.
