University Research in Quantum Computing Assists the Study of Genetic Diseases
(CavalierDaily) Stephan Bekiranov, computational biologist and associate professor, has developed an algorithm that utilizes a quantum computer in order to study genetic diseases. This algorithm was designed to introduce efficiencies in the computations by reducing the number of calculations performed in an operation. This breakthrough opens up possibilities for researchers in the medical and genetics field to crunch data in a more faster and efficient manner, paving the way for more medical breakthroughs to be made.
The millions of structural units that make up DNA are called nucleotides. Ultimately, it is imperative that scientists study and identify the nucleotide differences in DNA in order to develop ways to treat genetic diseases. However, genetic data is vast, so computations are essential for analyzing it.
Genetic information is vast and often on the scale of billions of bits, the time taken to process data by his algorithm is exponentially reduced. While a conventional computer would have to perform three billion operations on a computation of genetic data, this algorithm would only take 32 operations in a quantum computer, thus leading to an exponential gain in processing time.
Bekiranov has a doctorate in theoretical physics and has studied quantum mechanics, but 20 years ago, he transitioned into computational biology, which has now been his focus of study. He has been working on this project in quantum computing for one year.