Evidence map›Paper›PMID 42182512›Full record

ArticlebioRxiv : the preprint server for biology2026

Nanopore event detection in a simple and adaptive way.

Peijia Wei, Mayukh Kansari, Michael Mierzejewski, Tobias Ensslen, Chih-Yuan Lin, Kyril Kavetsky, Peter D Jones, Jan C Behrends, Marija Drndić, Maria Fyta

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Peijia WeiComputational Biotechnology, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany.ORCID 0009-0006-1120-940X
Mayukh KansariComputational Biotechnology, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany.
Michael MierzejewskiNMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany.
Tobias EnsslenLaboratory for Membrane Physiology and Technology, Department of Physiology II, Faculty of Medicine, University of Freiburg, Hermann-Herder-Str. 7, 79104 Freiburg, Germany.
Chih-Yuan LinDepartment of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Kyril KavetskyDepartment of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Peter D JonesNMI Natural and Medical Sciences Institute at the University of Tübingen, 72770 Reutlingen, Germany.
Jan C BehrendsLaboratory for Membrane Physiology and Technology, Department of Physiology II, Faculty of Medicine, University of Freiburg, Hermann-Herder-Str. 7, 79104 Freiburg, Germany.
Marija DrndićDepartment of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Maria FytaComputational Biotechnology, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany and Center for Computational Life Sciences, RWTH Aachen University, Pauwelstrasse 19, 52074 Aachen, Germany.

Funding

Enzymeless, controlled electrostatic ratcheting in solid-state nanoporesR01HG012413 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DRNDIC, MARIJA, SHEPARD, KENNETH L · 2022 to 2025
$3.1M
NHGRI NIH HHS R01 HG012413
6 · The paper itself

Abstract

Nanopore read-out, that is the current signals measured across nanometer-sized openings in dielectric membranes or through natural protein channels, enables the detection, identification and sequencing of individual molecules. The detection can take place by analyzing the events of single biomolecules interacting with the pore. The accuracy in the detection of these single events is key for identification of physicochemical properties of analyte molecules. To this end, we further develop a very simple, fast, almost parameter-free, and adaptable cluster-based event detection (CBED) algorithm that clusters the nanopore signals prior to detecting nanopore events. The algorithm is validated against two other event detection schemes with respect to simplicity and efficiency. For this, nanopore data from four different experiments stemming from different laboratories that vary in the nanopore type, size, and analyte are considered. The comparison is made on the basis of the number of events detected, their quality, and the most important features extracted from nanopore events. Our results underline the higher efficiency and less noise of the CBED detected events for biological nanopore data and the need for an on-the-fly adaptivity of the baseline current for a class of solid-state nanopore data.

Identifiers

PMID42182512
PMCPMC13192963

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Registered trials

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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.