Similar to me. I started with MATLAB (I even worked for them for a time), but then moved to Python when I started working more in Bioinformatics and lately expl

Similar to me. I started with MATLAB (I even worked for them for a time), but then moved to Python when I started working more in Bioinformatics and lately explore Julia a lot. The current issue with Julia is that most of the tutorials and docs available on the web are targeted at developers, not users, and therefore has a hard time converting the more casual MATLAB and, to a lesser degree, Python users. The major advantage of MATLAB over any of the other languages is its integration with the MATLAB Desktop and the casual simplicity for non-programmers. I don't really have to worry about data types, it seems to be working out of the box (which is an advantage for beginners but a serious handicap at a later stage). Julia has a higher initial barrier to adoption with its many different paths to success). Though I suspect that especially with its macros julia will be able to create extremely intuitive and expressive packages for all kinds of problem domains. I think a good start for julia would be to include more workflow-oriented tutorials in the docs that also provide a path through the current mess of packages (220 at current count, with sometimes quite redundant functionality, e.g., Gadfly, Winston, pyplot, Gaston). Heck, maybe I should just help with it once I'm done with my current project.