I’m currently an undergrad majoring in genetics and math. The math major at my university allows a fair amount of choice when it comes to which classes I take and when I take them. I completed three years of calculus and a combinatorics course at the university while I was in high school through a special program, so now I basically get to pick whatever upper division classes I want, as long as I take enough to complete the major. I’m currently taking a course in probability theory, and next semester I’ll take either theory of statistics or stochastic processes. What sorts of math would be most useful in genetics and cell biology? What will look good when I apply to grad school for biology?
Umm, it all looks damn good to me, but if I had to hazard a guess I’d say anything stats-related is going to be of great value, not only for yourself, but perhaps for many of your peers, who will have, at best, a rudimentary working knowledge of how to get nice-looking error bars using GraphPad.
Probability, statistics, linear algebra, and differential equations are probably the big four. You’ll get more combinatorics along the way as well.
You may also want to look into your university’s computer science classes. Bioinformatics is big now and getting bigger. Classes in programming and algorithms would serve you well there.
Statistics has a huge application not only in science, but in everyday life as well. People lie with statistics all the time; being able to catch them is a good way to avoid getting taken.
All the stuff from the previous posters. Let me throw in a class from my Alma Mater…
MAT 485, 486: Mathematical Modeling and Simulation I (4) II (4) WSp
Introduction to the general principles of modeling. Models will be selected from the areas such as physics, biology, political science, chemistry, engineering, and business. Analytical, numerical, and simulation methods will be used to solve the models. 4 lecture/problems. Prerequisites: C or better in the following courses: CS 120 or CS 125, MAT 201, MAT 208, MAT 216, and STA 330 or consent of instructor.
Probability / Statistics: Design of Experiments, Linear Models, Bayesian Theory, Sampling Theory, Time Series Analysis, Advanced Probability Models,
Be an Excel expert and know SAS quite well.