By applying machine learning algorithms to vast genomic data, researchers discovered 70,500 previously unknown RNA viruses, illustrating AI's powerful role in exploring unexplored viral diversity.
The study underscores a revolution in virology, showcasing a ‘bottomless pit’ of untapped viruses that could hold answers to uncharacterized diseases and unexplained health issues.
Employing AI tools like ESMFold to predict protein structures, researchers are capturing the evolving complexities of RNA viruses, indicating that traditional identification methods are increasingly insufficient.
Babaian warns that many RNA viruses may be overlooked by current methods, emphasizing that continuous innovation in viral detection is crucial in understanding and mitigating potential health risks.
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