ArticlebioRxiv : the preprint server for biology2025
An Accessible Python Framework for Real-Time Magnetic Tweezers Microscope Control and Image Processing.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
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Abstract
Magnetic tweezers are a popular biophysical instrument for manipulating and measuring single molecules. Most groups rely on custom-built setups tailored to specific experiments, making it challenging to implement and share software. Typically, image acquisition and hardware control are automated via LabVIEW, while real-time video processing is implemented in C++/CUDA libraries. Live processing can eliminate the need to store raw video, enabling high throughput, fast acquisition rates, and simplified experimental workflows. However, no open-source general-purpose software framework currently unifies these capabilities for magnetic tweezers experiments. Here, we introduce MagTrack and MagScope open-source Python-based tools designed to fill this gap. MagTrack is an image-processing library that efficiently determines bead-positions from magnetic-tweezers videos using CPU and/or GPU computation. MagScope is a comprehensive software framework offering a graphical user interface, real-time hardware control, data acquisition, and video processing. It is built on a multiprocessing architecture for responsive, high-throughput computation. Together, MagTrack and MagScope offer a fully customizable, end-to-end, open-source Python alternative to proprietary or fragmented systems, enabling laboratories to adapt and extend the framework according to their experimental needs.
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