Skip to main content

Research Repository

Advanced Search

Quantum computing at the frontiers of biological sciences

Emani, Prashant S.; Warrell, Jonathan; Anticevic, Alan; Bekiranov, Stefan; Gandal, Michael; McConnell, Michael J.; Sapiro, Guillermo; Aspuru-Guzik, Al�n; Baker, Justin T.; Bastiani, Matteo; Murray, John; Sotiropoulos, Stamatios N; Taylor, Jacob; Senthil, Geetha; Lehner, Thomas; Gerstein, Mark B.; Harrow, Aram W.

Quantum computing at the frontiers of biological sciences Thumbnail


Authors

Prashant S. Emani

Jonathan Warrell

Alan Anticevic

Stefan Bekiranov

Michael Gandal

Michael J. McConnell

Guillermo Sapiro

Al�n Aspuru-Guzik

Justin T. Baker

Matteo Bastiani

John Murray

Jacob Taylor

Geetha Senthil

Thomas Lehner

Mark B. Gerstein

Aram W. Harrow



Abstract

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences.

Citation

Emani, P. S., Warrell, J., Anticevic, A., Bekiranov, S., Gandal, M., McConnell, M. J., …Harrow, A. W. (2021). Quantum computing at the frontiers of biological sciences. Nature Methods, 18, 701-709. https://doi.org/10.1038/s41592-020-01004-3

Journal Article Type Article
Acceptance Date Oct 22, 2020
Online Publication Date Jan 4, 2021
Publication Date 2021-07
Deposit Date Oct 23, 2020
Publicly Available Date Mar 28, 2024
Journal Nature Methods
Print ISSN 1548-7091
Electronic ISSN 1548-7105
Publisher Nature Publishing Group
Peer Reviewed Peer Reviewed
Volume 18
Pages 701-709
DOI https://doi.org/10.1038/s41592-020-01004-3
Public URL https://nottingham-repository.worktribe.com/output/4986166
Publisher URL https://www.nature.com/articles/s41592-020-01004-3

Files




You might also like



Downloadable Citations