London, January 29: Google DeepMind unveiled a pioneering artificial intelligence tool named AlphaGenome, designed to interpret vast strands of DNA and predict how subtle mutations influence biological processes. The programme can analyse up to a million base pairs at once, allowing scientists to observe how specific genetic changes drive diseases.

The technology is expected to usher in a new era of personalised medicine by enabling the creation of synthetic DNA. These "designer" sequences can be engineered to activate or deactivate genes in specific parts of the body, a level of precision that current gene therapy methods cannot achieve. Nipah Virus Outbreak Contained in West Bengal: Health Ministry Confirms Only Two Cases Since December; Asian Countries Tighten Screenings.

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Ziga Avsec, lead of the genomics initiative at DeepMind, explained that AlphaGenome could generate short stretches of non-coding DNA that do not exist in nature. These synthetic sequences act as a "switch" within a delivery vector, ensuring that a therapeutic gene only activates in target tissues, such as the liver or retina, while remaining inactive elsewhere in the body.

The breakthrough is particularly significant because it addresses the "dark genome," the 98 per cent of genetic material previously dismissed as "junk DNA." While only two per cent of the genome codes for proteins, research now shows that the regulatory elements within the non-coding regions play a critical role in human health and the development of diseases.

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AlphaGenome was trained using both human and mouse genomes to understand how different sequences drive various biological functions. Dr Robert Goldstone, head of genomics at the Francis Crick Institute, described the model as a major milestone that moves genomic AI from theoretical interest to practical utility for studying complex diseases. Arctic Scientists 'feel Pretty Uncomfortable' on Greenland.

The research, published in the journal Nature, has also drawn praise from the wider scientific community. Experts believe the tool will provide vast new datasets to help identify beneficial genetic changes, potentially leading to the development of entirely new classes of medical therapies and a deeper understanding of plant and microbial biology.

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