Quantum Computing to study genetic diseases

Researchers at the University of Virginia School of Medicine are tapping into the potential of quantum computers to understand genetic diseases.

The team developed and implemented a genetic sample classification algorithm, a Hamming distance-like, that is fundamental to the field of machine learning on a quantum computer in a very natural way using the inherent strengths of quantum computers.

The new algorithm essentially classifies genomic data. It can determine if a test sample comes from a disease or control sample exponentially faster than a conventional computer. For example, if they used all four building blocks of DNA for the classification, a conventional computer would execute 3 billion operations to classify the sample. The new quantum algorithm would need only 32. (GEN)

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