making the most of scientific software
Hi everyone. I am a graduate student at the University of Washington studying computational and theoretical neuroscience, and over the past few years I’ve done a lot of experimenting with different programming languages and tools to aid me along the way. I’ve tested out a lot of different directions and taken fair number of missteps, but I wanted to start this blog to document and share some of what I’ve learned.
Most of what I’ll talk about will be geared toward making the computational side of science more accessible and the analyses more reproducible. I will therefore focus principally the design of code bases and workflows, as opposed to, for example, the implementation of specific algorithms. My motivation for doing this is that while software and workflow design have received a tremendous amount of attention in commercial software development, they have a relatively minimal presence in the scientific setting, despite their paramount importance. This is no one’s fault in particular, given the vastly different pressures in the academic research environment, but that doesn’t mean that we can’t take a stab at making things better. In this blog, my goal is simply to voice some of the methods that I have found to work well for me, with the hope that they might help others expedite their own journeys in silico. And of course, questions and comments are more than welcome.
Until next time.