Tag Archives: publish or perish

FOSS and research

I’ve been wondering about why FOSS is often compared to the academic world, but at least in my limited experience, I see little people that grasp its concept in the world of research. On a quick look, developing FOSS in a research environment would be very good: not only you’d get publicly available results when you publish, but at the same time you can make sure that in an extreme case your application will be carried on by someone else should you not be able to continue development.

At least in the life sciences, it’s hard to see such a mentality. I can understand , but at the same time, ? For me, such an idea would be optimal. Once the paper is out, you can release your software (GPL would be best) and make sure someone will improve or mantain in. Of course you won’t be able to publish for each upgrade you do, but I would generally think of that as a bad policy, one made just to increase the publication count.

Does something like that happen with FOSS in other research areas?

Brain drain

There is always a lot of talk about “brain drain” (fuga di cervelli in Italian) from my country. I keep on reading disgruntled comments of low pays and poor research, and that going abroad is the only solution for an Italian scientist to be successful.

While I believe that research done outside of my country can be handled better (but it’s impossible to know for sure: never tar everyone with the same brush), I think that, also thanks to the way the media and the scientists themselves handle it, in everyone’s view it has almost become like the El Dorado. And that, in my opinion, is incorrect.

Continue reading

Buggy bioinformatics software

As people who read my science-related posts know already, I’m not a big fan of {{post id=”software-and-biological-research” text=”software made just to support a publication”}}. Recently I’ve stumbled again into similar software. Namely, I’m talking about the TIGR Multiexperiment Viewer (TMeV), a Java-based program which is often used for microarray analysis. It’s not exactly “fit for publication”, because it has reached version 4 last year, but shows some of the problems ({{post id=”genbugg” text=”mentioned already”}}) with releasing bioinformatics software.

I use TMeV mostly because I didn’t find any other implementation of the hierarchical clustering algorithm with support trees. However, I’ve stumbled upon a very annoying bug in the most recent version. Normally I use average linkage clustering and as the distance metric I employ the Pearson’s correlation, and with gene and sample bootstrapping: with certain files this makes TMeV report errors at random during the iterations.

Continue reading