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New research by NTT Data suggests a combination of quantum and classic computers gave the best results when assembling a genome, giving hope that these machines can benefit healthcare.
A new quantum computing project suggests these powerful machines can help the healthcare sector by optimising the genome assembly process.
That’s according to NTT Data, which claims its latest research is a “milestone” in the use of quantum computing for healthcare and life sciences.
The company said digital representations of genome sequences can be investigated by scientists to identify genetic variations associated with certain illnesses, which could lead to new treatments and therapies for genetic diseases.
The NTT Data project explored the feasibility of using quantum computing for assembling the genome by comparing quantum and non-quantum computing approaches. Two approaches were used to generate the genome of a bacteriophage called phiX174.
For the quantum approach, NTT Data used a D-Wave quantum computer and a process called quantum annealing to find solutions to problems. The results from this approach were compared with a non-quantum method using classical computers.
The results of this proof-of-concept study suggest that purely quantum approaches still present difficulties in tackling large problems. NTT Data said that an improvement in processing time was observed when the computational capacity increased, but this was “exponential” in traditional systems and “almost linear” in quantum systems.
However, the results suggested that a hybrid approach – using both quantum and classic systems – was able to find optimal solutions for problems of various sizes. NTT Data said this suggests that quantum computing could present an alternative way to solve large optimisation problems in areas like biology and health.
“Overall, the results obtained with the different solvers look promising in many respects, but at the same time highlight the importance of choosing an appropriate solver for the problem and the need for further research to improve the scalability of the quantum and quantum-inspired solvers,” NTT Data said in a report.
It has been hoped for decades that by improving our knowledge of the human genome, scientists can better understand genetic variations and the potential impact on disease. Last year, scientists published the first complete, “gapless” sequence of the human genome, nearly 20 years after the Human Genome Project created the first draft sequence.
Meanwhile, a team of scientists recently claimed they achieved a breakthrough towards fault-free quantum computers, by using new error-detecting code to accurately simulate a hydrogen molecule
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