Evidence map›Paper›PMID 41939294›Full record

ArticleComputational and structural biotechnology journal2026

SMITracker: An Interactive Platform for Tracking and Analysis of Single-Molecule Interactions with Linear Substrates.

Arash Ahmadi, Magnar Bjørås, Bjørn Dalhus

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 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

3 authors.

Arash AhmadiCentre for Computational and Data Science (dScience), Faculty of Mathematics and Natural Sciences, University of Oslo, N-0316 Oslo, Norway.ORCID https://orcid.org/0000-0001-5566-7775
Magnar BjøråsDepartment of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), N-7491 Trondheim, Norway.ORCID https://orcid.org/6603694044
Bjørn DalhusDepartment of Microbiology, Oslo University Hospital HF, Rikshospitalet and University of Oslo, N-0424 Oslo, Norway.ORCID https://orcid.org/0000-0002-9867-8391

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the interactions of proteins with macromolecular substrates such as DNA, microtubules, and actin filaments is critically important in molecular biology and beyond. Single-molecule experiments provide unprecedented insight into the dynamics of these interactions. However, efficient analysis of large datasets generated by such experiments remains a major challenge. Specifically, in single-molecule experiments that involve scanning of such linear substrates, the absence of a comprehensive and effective system for detecting interactions among millions of frames of high-frequency imaging data and excluding noise without bias hampers research productivity and data quality. To address these limitations, we introduce "Single-Molecule Interaction Tracker (SMITracker)", an interactive analysis platform designed to enable efficient, accurate, and scalable detection of single-molecule interaction events. The protocol begins with raw image data obtained from single-molecule experiments, which undergoes preprocessing and is transformed into a structured dataset, suitable for processing in R. Using an automatic trajectory detection algorithm and a uniform noise exclusion model, the target data are detected and organized for further analysis. Final outputs include comprehensive diffusion analysis and informative visualization, enabling side-by-side comparison of different proteins and/or experimental conditions. SMITracker is available as an R package for R users and as a Docker image for non-R users, offering a highly effective and convenient solution to the common challenges in analyzing data from single-molecule experiments.

Identifiers

PMID41939294
PMCPMC13047747

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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.