Google DeepMind's AlphaGenome, launched recently, signifies a shift towards open genomics by making advanced genomic analysis tools accessible via API for non-commercial research. This AI model excels at decoding previously hard-to-read sections of DNA, often dismissed as 'junk', by analyzing up to a million base pairs simultaneously and significantly enhancing the understanding of gene regulation and disease prediction. It outperformed existing models in numerous benchmarks by accurately predicting gene expression and variant effects, allowing for faster discoveries in genetic disorders and personalized medicine. The architectural design employs a U-Net-inspired neural network with 450 million trainable parameters optimized for genomic data, making it less resource-intensive than previous models. AlphaGenome demonstrates the potential impact of AI in genomics, emphasizing its role in revealing the complex interactions in the non-coding genome that regulate cell functions and disease risk.

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