Machine Learning-Driven Nanopore Sensing for Quantitative, Label-Free miRNA Detection.
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| Title: | Machine Learning-Driven Nanopore Sensing for Quantitative, Label-Free miRNA Detection. |
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| Authors: | Koch C; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK.; Department of Life Science, Sir Alexander Fleming Building, Imperial College London, London, UK., Sakthimani S; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK., Noakes VM; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK., Cretu M; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK., Newman D; Oxford Nanopore Technologies, Oxford, UK., Gutierrez R; Oxford Nanopore Technologies, Oxford, UK., Bruce M; Oxford Nanopore Technologies, Oxford, UK., Gorelik J; National Heart and Lung Institute, ICTEM, Imperial College London, London, UK., Guerra N; Department of Life Science, Sir Alexander Fleming Building, Imperial College London, London, UK., Edel JB; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK., Ivanov AP; Department of Chemistry, Molecular Science Research Hub, Imperial College London, London, UK. |
| Source: | Small methods [Small Methods] 2026 Feb; Vol. 10 (4), pp. e02335. Date of Electronic Publication: 2026 Jan 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: WILEY-VCH Verlag GmbH & Co. KGaA Country of Publication: Germany NLM ID: 101724536 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2366-9608 (Electronic) Linking ISSN: 23669608 NLM ISO Abbreviation: Small Methods Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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