I'm a PhD candidate studying bioinformatics/bioengineering. My research involves mining massive amounts existing data on proteins for the purposes of computationally designing novel proteins. Beyond this I'm interested in computationally designing proteins (and other molecules) for use in synthetic biology, nanomaterials and therapeutics.
I use Python for most of my research. It is simple, making coding quick. As long as good programming practices are followed, the code is highly readable. There are tons of great packages, especially for scientific computing and bioinformatics. There are a number of interactive modes (e.g. iPython) which enable interactive exploratory data analysis. Prody (http://prody.csb.pitt.edu/), Biopython (http://biopython.org/wiki/) and PyRosetta (http://www.pyrosetta.org/) are few of the Python packages that I use on a regular basis. Due to the large amount of data that I deal with, I often write programs in C++ to speed things up. I recently came across the Nim programming language, an expressive, statically typed language with a simple syntax (similar in many ways to Python). It may be a good fit for the field of bioinformatics (and more generally scientific computing), offering both speed and ease of use.
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Last seen Oct 5 '17 at 20:13