Scientists at the University of Virginia University of Medicine have developed an algorithm that can shed significant light on genetic diseases, as well as help physicians and medical experts make rapid diagnoses. And it can be a game-changer – once someone builds a computer powerful enough to actually run it, ie.
The algorithm in question is one that is designed to analyze genomic data. It can be used to determine if a test specimen comes from a person with a disease or healthy controls and is significantly faster than current conventional computers.
“[Our] The algorithm classifies a person as a disease or is not based on the occurrence of genetic changes in the person’s genome, ”UVA associate professor Stefan Bekirnov told . “In principle, it can be applied to predict the disease as well as a patient’s genetic predisposition.”
For example, remember that a middle-aged patient with memory loss visits a clinic. His physician and family are concerned about possible early Alzheimer’s disease. Blood is drawn to the patient, and DNA and RNA are extracted and sequenced. Then they wait. And wait.
Today, this process may take a few weeks or even months to reach an answer. But using new algorithms developed by UVA researchers, the process – which involves scanning vast genomic, cellular databases to make the necessary estimates – can be successfully completed in just a few hours.
Quantum road
So what is the road? After all, the great thing about today’s over-the-air updates and the constantly tweaked, cloud-based algorithms (Google alone rolls out some 500 to 600 changes to its search algorithm each year) is that they are getting faster. Can be deployed from. However, the problem with the UVA algorithm is that it cannot yet be called into action – because the computer that is better equipped to run it does not yet exist.
This is because it is an algorithm designed for a quantum computer: a class of next-generation supercomputers that are currently in their relative infancy. Unlike a classical computer, which encodes a series of people and information as zeros, quantum computer bits (called qubits) can contain either one, one zero, or both simultaneously. These qubits are made up of sub-atomic particles, which conform to the laws of quantum rather than classical, mechanics.
The expectation with quantum computers is that they will be able to complete the quirk quickly. This is because their superposition property (in which quantum particles are present in multiple overlapping states at the same time) allows the qubits of a quantum computer to make multiple guesses at once while solving problems. This is much better than the time-consuming, trial and error computations of classical computing that can only make one guess at a time.
“Sure, no one can run it now, but it will be worth waiting for when it finally arrives.”
Quantum computers can be highly important for difficult challenges such as cryptography and particle physics. In both of these cases, quantum computers promise to help solve heavy computational condenses in a fraction of the time of their classical counterparts. But this work – the first published quantum computer study funded by the National Institutes of Mental Health and, possibly, using a universal quantum computer funded by the National Institutes of Health – shows that quantum computers also exist in fields such as biochemistry and the like. How they can prove useful. molecular Genetics.
“Our study serves as a marker, expanding interest in quantum computing while it is still in a nascent stage of development,” said Bekiranov.
From toy applications to real ones
The UVA algorithm has been tested on IBM’s quantum computer. In theory the complete algorithm can be run on an existing quantum computer. But the problem is that it can only run on the “toy” problem, not a real one close to the complexity required in the real world.
Bekiranov noted that there are several current constraints for using algorithms. For starters, quantum logic gates (basic quantum circuits that operate in very small numbers) do not operate with correct fidelity, resulting in errors in measured results and predictions as well. Even the number of qubits on the most powerful quantum computer is currently severely affected. This limits researchers to lower genomic resolution. Also, telling the quantum computer to perform too many gate operations causes the quantum state to “decourage” the middle of the computation, thereby destroying it.
“Finally,” said Bakiranov, “and it looks crazy, [but] It can take a complex set of gate operations to input our data into a quantum computer. In fact, depending on the data, it may require so many gates to be implemented that this may negate the advantage of our quantum algorithm. “
While it may seem disappointing, however, he said that with enough steady progress along the way and significant scientific breakthroughs, a quantum computer might be able to run it properly “within a decade”. Think of it as making an amazing app for the iPhone that doesn’t ship until 2030. Sure, no one can run it right now, but the wait will be worth it when it finally arrives.
Just put the “groundbreaking genetic diagnosis tool” down as another reason to get excited about the upcoming quantum computing revolution.
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