There’s a blog meme going around concerning the mathematical education of biologists – interesting discussion here (Keith), here (Deepak) and here (RPM).

In my experience, you pick up the maths that you need during the course of your research. That makes the question “what maths should undergraduate biologists learn?” rather difficult to answer – but I think we’re all agreed that one response is “more than they do now”. Anyway, on to those meme questions and I’m with Deepak – it’s maths, not math:

- Are you a biologist, if so what kind?
- What math did you take in college?
- What math do you use?
- What math do you wish you’d studied?
- How do you use math in your job (or research)?

I was trained in biochemistry (B.Sc. and Ph.D.). These days I call myself a bioinformatician, if I have to call myself anything. I hesitate to call myself a biologist because (a) I don’t like labels, (b) I believe in “one science” – no disciplines, just scientists and (c) my mental wavelength has always been more in tune with physicists and computer programmers than biologists.

An introductory first year course called “physics, mathematics and statistics for biologists”. It was at a far lower level than A-level (the advanced subjects that students in the UK study at high school aged 16-18). It was taught with no enthusiasm from the staff because they knew that most people studied biology precisely because they hated maths and physics.

Whatever I need, as and when I need it. I don’t have strong mathematical intuition – in fact I’ve always found formal mathematics courses quite difficult. In later life, I’ve discovered my own way of learning the maths that I need: I plot graphs to help me understand equations, I run small “trial and error” tests with some sample numbers when developing algorithms. Of course I have a great resource now that I didn’t have as an undergraduate – the Web, where I can browse tutorials for maths courses from universities anywhere in the world, read the manuals of statistical packages, get Wikipedia definitions and so on.

Multivariate statistics. Virtually all real-world biological problems are multivariate. I’ve never understood why most biology undergraduates are taught only the most rudimentary, basic statistical methods.

Mostly statistics, mostly using the R project and mostly for analysing protein sequences and structures. I also use software with a lot of underlying mathematics (such as molecular dynamics simulation), where I’m not exposed directly to the mathematical theory. I don’t believe that I’ve ever required calculus, complex algebra or had to figure out whether a wooden block will slide down a slope as part of a research problem – but that could change, depending on where the research takes me.

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