Decades after researches first sequenced the human genome, scientists throughout the world are still working to understand it. Despite diligent global efforts to link uncommon variations in DNA sequences with human disease, progress has been slow, in large part due to limitations in scientific understanding and in part due to limitations in computational technologies.
Artificial intelligence has the potential to help scientists decipher the millions of genetic variations present in the genomes of different people in order to identify which ones lead to disease and which ones do not. In order to fully exploit the power of AI, however, scientists need to compare the genomes of thousands or tens of thousands of people. This task not only requires intense computational effort, it is also prone to error and will take years to complete.
Quantum computing has the potential to facilitate that process. We are researchers with a long-standing interest in finding ways to use genetics in the clinic and developing new technologies to study the human genome. Combining quantum computing with AI has the potential to accelerate genomic analysis far beyond traditional methods. For time-sensitive medical conditions, faster decoding of genetic information can directly inform urgent treatment decisions and, in some cases, be lifesaving.
Conventional vs. quantum computing
In conventional computing, individual bits of information – binary digits, also called bits – can represent only two states: namely, 0 and 1.
However, the qubits used in quantum computing can have more than two distinct states. Adding qubits together increases the number of states exponentially. The power of quantum computers lies in being able to check all the possibilities at once for problems with large numbers of variables, rather than one at a time like even the fastest possible classical computer must do. This allows quantum computers to solve certain types of problems, such as factoring large numbers for today’s encryption schemes and performing combinatorial optimization to find the best route through a large number of points.
Quantum computers work much differently from the computer you’re likely using to read this article.
Still, quantum computing is currently in its infancy. Despite the enormous potential of this technology, computer scientists are dealing with challenges related to its scalability, error correction, hardware development and the setting of standards.
There are also significant time and cost constraints associated with ameliorating these challenges. Experts in the field estimate that it may be at least a decade before quantum computing will be truly useful outside of the laboratory.
Bigger and better data analysis
If researchers are able to overcome these challenges, combining AI and quantum computing may not only enable scientists and clinicians to better understand the human…
