Print Email Facebook Twitter A Generalized Transformer-Based Pulse Detection Algorithm Title A Generalized Transformer-Based Pulse Detection Algorithm Author Dematties, Dario (Northwestern University; Argonne National Laboratory) Wen, C. (TU Delft BN/Cees Dekker Lab; Wageningen University & Research; Kavli institute of nanoscience Delft) Zhang, Shi Li (Uppsala University) Date 2022 Abstract Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction. Subject artificial neural networkgeneralized algorithmmachine learningnanopore sensingspike recognitiontransformer To reference this document use: http://resolver.tudelft.nl/uuid:137b9cb7-cfd0-4659-a641-426156e5e277 DOI https://doi.org/10.1021/acssensors.2c01218 ISSN 2379-3694 Source ACS Sensors, 7 (9), 2710-2720 Part of collection Institutional Repository Document type journal article Rights © 2022 Dario Dematties, C. Wen, Shi Li Zhang Files PDF acssensors.2c01218.pdf 3.51 MB Close viewer /islandora/object/uuid:137b9cb7-cfd0-4659-a641-426156e5e277/datastream/OBJ/view