The prospects of quantum computing in computational molecular biology

Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all scientific disciplines. In this review, we examine how current quantum a...

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Main Authors: Outeiral Rubiera, C, Strahm, M, Shi, J, Morris, G, Benjamin, SC, Deane, CM
Format: Journal article
Language:English
Published: Wiley 2020
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author Outeiral Rubiera, C
Strahm, M
Shi, J
Morris, G
Benjamin, SC
Deane, CM
author_facet Outeiral Rubiera, C
Strahm, M
Shi, J
Morris, G
Benjamin, SC
Deane, CM
author_sort Outeiral Rubiera, C
collection OXFORD
description Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all scientific disciplines. In this review, we examine how current quantum algorithms could revolutionize computational biology and bioinformatics. There are potential benefits across the entire field, from the ability to process vast amounts of information and run machine learning algorithms far more efficiently, to algorithms for quantum simulation that are poised to improve computational calculations in drug discovery, to quantum algorithms for optimization that may advance fields from protein structure prediction to network analysis. However, these exciting prospects are susceptible to “hype,” and it is also important to recognize the caveats and challenges in this new technology. Our aim is to introduce the promise and limitations of emerging quantum computing technologies in the areas of computational molecular biology and bioinformatics.
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spelling oxford-uuid:9fcfe879-d852-4678-a21d-f9bc009d43be2022-03-27T02:00:44ZThe prospects of quantum computing in computational molecular biologyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9fcfe879-d852-4678-a21d-f9bc009d43beEnglishSymplectic ElementsWiley2020Outeiral Rubiera, CStrahm, MShi, JMorris, GBenjamin, SCDeane, CMQuantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all scientific disciplines. In this review, we examine how current quantum algorithms could revolutionize computational biology and bioinformatics. There are potential benefits across the entire field, from the ability to process vast amounts of information and run machine learning algorithms far more efficiently, to algorithms for quantum simulation that are poised to improve computational calculations in drug discovery, to quantum algorithms for optimization that may advance fields from protein structure prediction to network analysis. However, these exciting prospects are susceptible to “hype,” and it is also important to recognize the caveats and challenges in this new technology. Our aim is to introduce the promise and limitations of emerging quantum computing technologies in the areas of computational molecular biology and bioinformatics.
spellingShingle Outeiral Rubiera, C
Strahm, M
Shi, J
Morris, G
Benjamin, SC
Deane, CM
The prospects of quantum computing in computational molecular biology
title The prospects of quantum computing in computational molecular biology
title_full The prospects of quantum computing in computational molecular biology
title_fullStr The prospects of quantum computing in computational molecular biology
title_full_unstemmed The prospects of quantum computing in computational molecular biology
title_short The prospects of quantum computing in computational molecular biology
title_sort prospects of quantum computing in computational molecular biology
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