Authors
London, J. A., Singh, A. K., Svendsen, T. C., Tirtom, N. E., Root, Z. A., Fishel, R.
Abstract
Magnetic tweezers are a popular biophysical instrument for manipulating and measuring single molecules. Most laboratories rely on custom-built setups tailored to specific experiments, resulting in a variety of hardware and software implementations. Typically, image acquisition and hardware control are automated via LabVIEW and specialized C/C++/CUDA libraries for real-time video processing. Live processing eliminates 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 flexible, modern, and fully customizable open-source alternative to proprietary or fragmented systems, enabling laboratories to adapt and extend the framework according to their experimental and programming needs.
Preprint server:
bioRxiv
The authors list and abstract were imported from bioRxiv on 04 Nov 2025.
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