About Us

The following people have been involved in the SETLyze project.

Arjan Gittenberger

Project leader and contact (info@gimaris.com) at GiMaRIS.

Jonathan den Boer

Internship bioinformatics (Leiden University of Applied Science) student at GiMaRIS. Responsible for the intial development of the application (then called “Sesprere”).

  • Implemented analysis “Spot preference”.
  • Documentation (user manual, programmer’s manual and technical design).

Serrano Pereira

Internship bioinformatics (Leiden University of Applied Science) student at GiMaRIS (September to November 2010).

  • Optimization of the overall application (renamed “SETLyze”).
  • Moved from Tkinter to GTK+ for creating the graphical user interfaces.
  • Optimization of analysis “Spot preference”
  • Implementation of analysis “Attraction within species” and analysis “Attraction between species”.
  • Sphinx documentation (user manual, developer guide).
  • Technical design.
  • Distribution packages (source package, Windows installer).

Continued work on SETLyze in January 2013:

  • Code repository moved from Bazaar to Git.
  • Implementation of batch mode for analyses “Spot preference”, “Attraction within species” and “Attraction between species”. This has been parallelized with the multiprocessing module from Python’s standard library.
  • Overall optimization of the code.
  • Dropped the XML report exporter in favor of an improved reStructuredText report exporter.
  • Use a configuration file to save user preferences.
  • Release of version 1.0 in April 2013.

Adam van Adrichem and Fedde Schaeffer

Minor project / internship bioinformatics (Leiden University of Applied Science) students at GiMaRIS.

  • Reorganised the Bazaar repositories to be easier to copy, develop and track.
  • Implemented the cancel button in the progress bar of the analyses.
  • Implemented the possibility of reading Microsoft Office Excel 97–2004 workbooks.
  • Tried to make a start making the technical design match the actual implementation.
  • Looked into how the repetitions of Wilcoxon tests could be parallelised using the multiprocessing module from Python’s standard library.
  • Looked into how an analysis could be executed serially for all species in the database, to find out which species should be investigated more.
  • Release of version 0.2.