ArticleJournal of chemical information and modeling2021
Quantum Machine Learning Algorithms for Drug Discovery Applications.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Benchmarking Classical and Quantum Machine Learning for Potency Prediction across Ten Therapeutically Relevant Targets.ACS medicinal chemistry letters · 2026Article
- Quantum-machine-assisted drug discovery.npj drug discovery · 2026Review
- Quantum Computing in Drug Discovery Techniques, Challenges, and Emerging Opportunities.Current drug discovery technologies · 2026Review
- Quantum computing and the implementation of precision medicine.NPJ genomic medicine · 2025Review
- Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors.Nature biotechnology · 2025Article
- Quantum biological convergence: quantum computing accelerates KRAS inhibitor design.Signal transduction and targeted therapy · 2025Article
- Machine learning workflows beyond linear models in low-data regimes.Chemical science · 2025Article
- Self-Adaptive Quantum Kernel Principal Component Analysis for Compact Readout of Chemiresistive Sensor Arrays.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.Journal of chemical information and modeling · 2024Article
- Revolutionizing Healthcare: The Emerging Role of Quantum Computing in Enhancing Medical Technology and Treatment.Cureus · 2024Review
- A hybrid quantum computing pipeline for real world drug discovery.Scientific reports · 2024Article
- Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction.Journal of chemical theory and computation · 2024Article
- Learning from COVID-19: How drug hunters can prepare for the next pandemic.Drug discovery today · 2023Article
- Al-novation: Finding New Uses for Artificial Intelligence Across Industries.GEN biotechnology · 2022Article
- UV-adVISor: Attention-Based Recurrent Neural Networks to Predict UV-Vis Spectra.Analytical chemistry · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The growing quantity of public and private data sets focused on small molecules screened against biological targets or whole organisms provides a wealth of drug discovery relevant data. This is matched by the availability of machine learning algorithms such as Support Vector Machines (SVM) and Deep Neural Networks (DNN) that are computationally expensive to perform on very large data sets with thousands of molecular descriptors. Quantum computer (QC) algorithms have been proposed to offer an approach to accelerate quantum machine learning over classical computer (CC) algorithms, however with significant limitations. In the case of cheminformatics, which is widely used in drug discovery, one of the challenges to overcome is the need for compression of large numbers of molecular descriptors for use on a QC. Here, we show how to achieve compression with data sets using hundreds of molecules (SARS-CoV-2) to hundreds of thousands of molecules (whole cell screening data sets for plague and
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.