The prospects of quantum computing in computational molecular biology
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 May 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 2; 2025: 1; 2026: 1.
5 papers.
- 2025Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approachcited by 3
- 2021Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Mapscited by 2
- 2024Quantum-Inspired Machine Learning for Molecular Dockingcited by 0
- 2024Quantum-machine-assisted Drug Discoverycited by 0
- 2026Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMscited by 0
- 2026Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMs6 Aug 2026
- 2025Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach14 Apr 2025
- 2024Quantum-machine-assisted Drug Discovery24 Aug 2024
- 2024Quantum-Inspired Machine Learning for Molecular Docking22 Jan 2024
- 2021Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Maps21 Mar 2021