ArticleNature communications2021
Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- Quantum and nanoscale sensing of microinflammation for earlier detection of chronic inflammatory and neuroimmune disease.Discover nano · 2026Review
- AI-Driven Approaches for the Detection, Classification, and Surveillance of Viral Pathogens: Current Advances, Challenges, and Future Directions.Pathogens (Basel, Switzerland) · 2026Review
- A universal deep learning framework for empowering nanopore identification by reinforcing temporal signals.Nature communications · 2026Article
- Artificial intelligence-guided design of lipid nanoparticles for mRNA delivery.Acta pharmaceutica Sinica. B · 2026Review
- Machine Learning-Driven Nanopore Sensing for Quantitative, Label-Free miRNA Detection.Small methods · 2026Article
- Solid-state nanopore sensing reveals conformational changes induced by a mutation in a neuron-specific tRNAArg.Nucleic acids research · 2026Article
- NanoSSL: attention mechanism-based self-supervised learning method for protein identification using nanopores.Bioinformatics (Oxford, England) · 2026Article
- Metrology of Nanoscale Objects Using Nanopores.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Nanopore-based sensing for biomarker detection: from fundamental principles to translational diagnostics.Journal of nanobiotechnology · 2025Review
- Designing the Next Generation of Biomaterials through Nanoengineering.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Single-Molecule Protein Profiling Using Nanopores and Dimeric Aptamer-Modified DNA Carriers.Angewandte Chemie (International ed. in English) · 2025Article
- Clonal diversity shapes the tumour microenvironment leading to distinct immunotherapy responses in metastatic urothelial carcinoma.Nature communications · 2025Article
- Rapid diagnosis of ocular viral infections via single-virus detection using solid-state nanopore: A diagnostic evaluation study.PNAS nexus · 2025Article
- Nanopore Environmental Analysis.JACS Au · 2025Review
- Detection of protein oligomers with nanopores.Nature reviews. Chemistry · 2025Review
- Amplification-Free Quantification of Endogenous Mitochondrial DNA Copy Number Using Solid-State Nanopores.ACS nano · 2025Article
- Leveraging Artificial Intelligence and Gene Expression Analysis to Identify Some Potential Bovine Coronavirus (BCoV) Receptors and Host Cell Enzymes Potentially Involved in the Viral Replication and Tissue Tropism.International journal of molecular sciences · 2025Article
- Pioneering Role of Nanopore Single-Molecule Sensing in Environmental and Food Surveillance.Biosensors · 2025Review
- Characterizing Prion-Like Protein Aggregation: Emerging Nanopore-Based Approaches.Small methods · 2024Review
- A Robust Parallel Computing Data Extraction Framework for Nanopore Experiments.Small methods · 2024Article
Corrections and comments
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Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.
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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.