"In first quantum machine learning study with biological data, USC researchers leverage D-Wave to understand gene regulation
To date, much has been stated about the promise of quantum computing for myriad of applications but there have been few examples of a quantum advantage for real-world problems of practical interest. This might change with a new study from the USC Center for Quantum Information Science & Technology at the Viterbi School of Engineering and the USC Dana and David Dornsife College of Arts, Letters and Sciences. Researchers Richard Li, Rosa Di Felice, Remo Rohs, and Daniel Lidar have demonstrated how a quantum processor could be used as a predictive tool to assess a fundamental process in biology: the binding of gene regulatory proteins to the genome. This is one of the first documented examples in which a physical quantum processor has been applied to real biological data. The research was conducted on a D-Wave Two X machine at the USC Information Sciences Institute."
Read the news at USC Viterbi.