We distribute our software via GitHub: Below we describe the different software packages, with links to their associated papers and individual GitHub locations.


*** u-track (multiple-particle tracking) 

Multiple-particle tracking software designed to:

u-track software is profiled in this issue of Nature Methods.
  1. Track dense particle fields.
  2. Close gaps in particle trajectories resulting from detection failure.
  3. Capture particle merging and splitting events resulting from occlusion or genuine aggregation and dissociation events.

Its core is based on formulating correspondence problems as linear assignment problems and searching for a globally optimal solution. The software can be called either via a Graphical User Interface or command line.

For more information, please see Jaqaman et al., Nature Methods 5, pp. 695-702 (2008).


*** Diffusion mode analysis from frame-to-frame displacements

Diffusion analysis software designed to:

  1. Calculate the diffusion coefficient of a particle track from its frame-to-frame displacements.
  2. Categorize each particle track into a diffusion mode based on its diffusion coefficient (diffusion modes identified either manually or via analysis of the frame-to-frame displacement distribution).

For more information, please see Jaqaman et al., Molecular Biology of the Cell 27, pp. 1561-1569 (2016).


*** ColocP2C (colocalization analysis)

Colocalization analysis software designed to:

  1. Assess colocalization between two molecular entities from multi-channel high-resolution light microscopy images when one molecule has a punctate appearance while the other has a continuous appearance.
  2. Assess the above colocalization in the context of a third molecular entity (i.e. "conditional" colocalization).

For more information, please see Maringa-Githaka et al., Journal of Cell Science 129, pp. 4175-4189 (2016).


*** DC-MSS (transient motion analysis)

Transient motion analysis software designed to:

  1. Distinguish between free diffusion, confined diffusion, immobility and diffusion with drift.
  2. Segment tracks into subparts exhibiting the different motion classes.

For more information, please see Vega et al., Biophysical Journal 114, pp. 1018-1025 (2018).


*** FISIK (derivation of molecular interaction kinetics)

Framework for the Inference of in Situ Interaction Kinetics from single-molecule tracking data with sub-stoichiometric labeling. It consists of two components:

  1. A stochastic mathematical model of molecular movement and interactions, mimicking the biological system and data acquisition setup, including sub-stoichiometric labeling.
  2. Model Calibration with experimental single-molecule data to estimate molecular association and dissociation rates.

The supplied software implements the framework for a simple model of freely diffusing molecules in 2D. For more information, please see de Oliveira and Jaqaman, Biophysical Journal 117, pp. 1012-1028 (2019).


*** Detection of network-like biological structures

Software for the detection of lines and their intersections in network-like biological structures in light microscopy images, such as cytoskeletal filaments and meshworks or stained membranes in a cell sheet. Its key features include:

  1. Analytical derivation of multi-orientation information per pixel after curvilinear feature (i.e. ridge) filtering.
  2. Use of multi-orientation information from filters with different spatial localizations in order to balance orientation resolution and spatial localization.
  3. Parsimonious segmentation of lines and their intersections of arbitrary geometry.

For more information, please see Kittisopikul et al., Bioinformatics, Online ahead of print (2020).