ArticleBiosensors2020
Machine Learning to Improve the Sensing of Biomolecules by Conical Track-Etched Nanopore.
Article in Biosensors, 2020. 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.
- The evolution of nanopore measurements: from biological out-of-plane pores to plastic in-plane pores.Lab on a chip · 2026Review
- Solid-state nanopore sensing reveals conformational changes induced by a mutation in a neuron-specific tRNAArg.Nucleic acids research · 2026Article
- Nanopore sensing of protein and peptide conformation for point-of-care applications.Nature communications · 2025Review
- Amplification-Free Quantification of Endogenous Mitochondrial DNA Copy Number Using Solid-State Nanopores.ACS nano · 2025Article
- Nanopipettes as a Potential Diagnostic Tool for Selective Nanopore Detection of Biomolecules.Biosensors · 2024Review
- Single-Molecule Bioelectronic Sensors with AI-Aided Data Analysis: Convergence and Challenges.Precision chemistry · 2024Review
- Machine learning empowered next generation DNA sequencing: perspective and prospectus.Chemical science · 2024Review
- Identification and Detection of a Peptide Biomarker and Its Enantiomer by Nanopore.ACS central science · 2024Article
- Seeing the Invisibles: Detection of Peptide Enantiomers, Diastereomers, and Isobaric Ring Formation in Lanthipeptides Using Nanopores.Journal of the American Chemical Society · 2023Article
- Nanopore Discrimination of Coagulation Biomarker Derivatives and Characterization of a Post-Translational Modification.ACS central science · 2023Article
- Nanopore fingerprinting of supramolecular DNA nanostructures.Biophysical journal · 2022Article
- Focus on using nanopore technology for societal health, environmental, and energy challenges.Nano research · 2022Review
- SERSNet: Surface-Enhanced Raman Spectroscopy Based Biomolecule Detection Using Deep Neural Network.Biosensors · 2021Article
- The NEOtrap - en route with a new single-molecule technique.iScience · 2021Review
- A Guide to Signal Processing Algorithms for Nanopore Sensors.ACS sensors · 2021Article
- Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.Nature communications · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single nanopore is a powerful platform to detect, discriminate and identify biomacromolecules. Among the different devices, the conical nanopores obtained by the track-etched technique on a polymer film are stable and easy to functionalize. However, these advantages are hampered by their high aspect ratio that avoids the discrimination of similar samples. Using machine learning, we demonstrate an improved resolution so that it can identify short single- and double-stranded DNA (10- and 40-mers). We have characterized each current blockade event by the relative intensity, dwell time, surface area and both the right and left slope. We show an overlap of the relative current blockade amplitudes and dwell time distributions that prevents their identification. We define the different parameters that characterize the events as features and the type of DNA sample as the target. By applying support-vector machines to discriminate each sample, we show accuracy between 50% and 72% by using two features that distinctly classify the data points. Finally, we achieved an increased accuracy (up to 82%) when five features were implemented.
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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.