TITLE: Is there any research in mathematical biology that isn't heavy in differential equations?
QUESTION [7 upvotes]: I'm near the end of my pure math undergrad trying to decide what sort of math I'm interested in for graduate school. I've always thought the idea of mathematical biology was cool, but it seems like a lot of it is steeped in differential equations, which I'm really not too big on. I know there's some genetics research related to statistics, too, but I'm more into pure math. I guess the question is, is there any area of mathematical biology that doesn't rely heavily on differential equations or statistics (and if so, could you provide reference material)?

REPLY [3 votes]: All the stuff I've seen involves birth-and-death Markov Chains, especially SIS (susceptible-infected-susceptible) and SIR (susceptible-infected-recovered) models, it involves probability theory, asymptotic convergence and recurrent equations. The applications are vast - population biology, immunology, viruses. See Wierman, Marchette (2004) on applications to computer viruses and Nasell (1996,1999) on virus propagation.