Essential software for biology grad students: Part I Overview
When I started grad school, I had no idea at the time just how much I’d learn doing a PhD. I’m not just talking about the “big picture” stuff: how to do research, design and conduct experiments, analyze data, and synthesize information. I mean all of the day-to-day skills associated with academic writing, data entry, and organization.
Over the next few weeks, I’ll explain a bit about the workflows I use and the various pieces of software that make my life quite a bit easier. After numerous discussions with colleagues over the years, providing various software and workflow recommendations to others, and attending (and running) various software workshops, it turns out I have a lot of suggestions for fellow biology grad students.
I’ll try to keep my recommendations general, because I think they are applicable not just to grad students in biology, but are also likely of interest to undergrads (even post-grads) in the sciences and perhaps elsewhere. I won’t put together detailed How-To’s, and I won’t be able to cover everything, but here’s an overview of what to expect:
- Part II will cover some essential computing basics: automated backups, using online (cloud) storage, and version control;
- Part III will deal with different writing tools including Microsoft Word, Libre Office Writer, Markdown, Pandoc, and LaTeX;
- Part IV will discuss reference management and citation software options;
- Part V will touch on using databases instead of spreadsheets;
- Part VI will delve into statistics software and the majestic use of R for stats, graphics, and (if I have time) get into using Sweave with R and LaTeX;
- Part VII will go into a little bit about programming and shell scripting;
- and finally, Part VIII will wrap things all up.
So stay tuned! I’m still fleshing out my ideas on some of these topics, so as we go along I look forward to comments and suggestions.

Dr. Chubaty is an ecologist and simulation modeller who builds spatial models of forest landscapes and the species that live in them. He completed his PhD at Simon Fraser University modelling host selection in mountain pine beetle (MPB), followed by postdoctoral research at Université Laval and Natural Resources Canada developing forecasting models of MPB spread.
He runs FOR-CAST Research & Analytics in Calgary, Canada. His recent work
includes LANDIS-II forest landscape simulation studies, landscape
connectivity modelling, and analyses of insect outbreak dynamics, to inform
land management and species-at-risk decisions. He writes open-source R
packages for this work, including grainscape for connectivity analysis,
landisutils for LANDIS-II simulations, and co-developed the SpaDES
simulation platform. He advocates for open data and reproducible workflows.