Acknowledgements

The Duderstadt Lab

In the Duderstadt lab we study molecular machines that reshape and remake chromosomes using structural, biochemical, and single-molecule approaches. The major part of our research relies on microscopy techniques. To analyse the generated data in a reliable and reproducible manner we developed the ‘Molecule ARchive Suite’ (Mars). More information about the research projects and the team can be found on our homepage.

Software

The Mars software utilizes features from other software packages as referenced in the respective documentation pages and tutorials. We should like to thank the ImageJ community for creating a fantastic platform for the development of image processing and analysis software. We are grateful for the recent development efforts of ImageJ2 and common frameworks that have greatly enhanced the applications across platforms. Special thanks go to Curtis Rueden and Jan Eglinger as well as Tobias Pietzsch for taking the time to answer the many questions that have come up during development and Curtis Rueden for helping to configure our repositories for integration with Travis and scijava maven.

Mars Core Connections

As highlighted in the repositories page Mars Core and/or Mars Rover depend on the following software packages.

Fiji
Schindelin, J.; Arganda-Carreras, I. & Frise, E. et al. (2012), “Fiji: an open-source platform for biological-image analysis”, Nature methods 9(7): 676-682, PMID 22743772

ImageJ
Rueden, CT.; Schindelin, J. & Hiner, MC. et al. (2017), “ImageJ2: ImageJ for the next generation of scientific image data”, BMC Bioinformatics 18: 529, PMID 29187165

ChartFX
A scientific charting librabry focused on performance optimised real-time data visualisation. https://github.com/GSI-CS-CO/chart-fx

Connections of Mars Rover with other Software Packages

Trackmate
Tinevez, JY.; Perry, N. & Schindelin, J. et al. (2017), “Trackmate: An open and extensible platform for single-particle tracking.”, Methods 115: 80-90, PMID 27713081

BigDataViewer
Pietzsch, T.; Saalfeld, S. & Preibisch, S. et al. (2015), “BigDataViewer: visualization and processing for large image data sets”, Nature Methods 12(6): 481-483, PMID 26020499

Documentation Site Template

The template of this documentation site is based on Vega.