Miniconda Installer

Orange has a new friend! It’s Miniconda, Anaconda’s little sister.


For a long time, the idea was to utilize the friendly nature of Miniconda to install Orange dependencies, which often misbehaved on some platforms. Miniconda provides Orange with Python 3.6 and conda installer, which is then used to handle everything Orange needs for proper functioning. So sssssss-mooth!

Miniconda Installer

Please know that our Miniconda installer is in a beta state, but we are inviting adventurous testers to try it and report any bugs they find to our issue tracker [there won’t be any of course! ūüėČ ].


Happy testing! ūüźć|ūüćä



Orange in Pavia, Italy

These days, we (Blaz Zupan and Marinka Zitnik, with full background support of entire Bioinformatics Lab) are running a three-day¬†course on Data Mining in Python. Riccardo Bellazzi, a professor at University of Pavia, a world-renown researcher in biomedical informatics, and most of all, a great friend, has invited us to run the elective course for Pavia’s¬†grad students. The enrollment¬†was, he says, overwhelming, as with over 50 students this is by far the best attended grad course at Pavia’s faculty of engineering in the past years.

We have opted for the hands-on course and a running it as a workshop. The lectures include a new, development version of Orange 3, and mix it with numpy, scikit-learn, matplotlib, networkx and bunch of other libraries. Course themes are classification, clustering, data projection and network analysis.




Workshops at Baylor College of Medicine

On May 22nd and May 23rd, we (Blaz Zupan and Janez Demsar, assisted by Marinka Zitnik and Balaji Santhanam) have given two hands-on workshops called Data Mining without Programming at Baylor College of Medicine in Houston, Texas.

Actually, there was a lot of programming, but no Python or alike. The workshop was designed for biomedical students and Baylor’s faculty members. We have presented a visual programming approach for development of data mining workflows for interactive data exploration. A three-hour workshop consisted of 15 data mining lessons on visual data exploration, classification, clustering, network analysis, and gene expression analytics. Each lesson focused on a particular data analysis task that the attendees solved with Orange.

The two workshops were organized by Baylor’s Computational and Integrative Biomedical Research Center. Over two days, the event was attended by a large audience of 120 attendees.