Forum:advice on course selection for a bioinformatics career.
Entering edit mode
11 months ago
Aaron • 0

Hey all! I’m a current freshman at the University of Maryland where I am studying Computer Science. An unique aspect of our degree program is that we are required to take 12 credits in a separate department ( 300 to 400 level) to utilize the interdisciplinary nature of computer science.

I am broadly interested in bioinformatics and am currently doing research in structural bioinformatics. I would like to do a PhD in computer science and then work as a research scientist or research engineer in industry doing ML/bioinformatics work. If that doesn’t work out I think being a software engineer at a biotech company could also be fulfilling.

I am considering three different options for my secondary concentration and I was hoping to get some advice over which selection of courses would best suit my career goals.


For this I would take:

MATH 405 - Linear Algebra (proof-based, already took introductory lin alg)

MATH 401 - Applications of Linear Algebra (incidence matrices, directed graphs, finite Markov chains are a few course topics)

STAT 401 - Applied Probability and Statistics II

MATH 4xx - not sure could do Number Theory, Advanced Calculus, Sampling Theory)

This seems to be the most logical as the Math background would help with AI and ML and it seems it is the hardest to learn on my own.


For this I would take:

BSCI 222 - Principles of Genetics (pre req)

BSCI 370 - Principles of Evolution (DNA protein and genome evolution)

BSCI 410 - Molecular Genetics (molecular basis of gene structure and function)

BSCI 426 - Human Genetics (focuses of specific human genetic topics using primary research papers)

BSCI 379 - Undergraduate Research (already completed, my PI is in the Bio department).

(all these Bio courses have Orgo as a prerequisite which I took last semester, so i assume they will go into the underlying chemistry and not just be memorizing terms like in intro bio)

My main question would be is this collection of bio courses something that would help me in my career? Specifically would being able to see the larger scope of the computational work I do be sufficient reason to choose this pathway?


This may be a weird one. One of the things I have discovered about college is that you don’t actually have to register for the class to still attend its lectures. I have been doing this for CMSC 701 our computational genomics class and I have been learning a ton doing this. I think this is a very effective way to learn content but not gain mastery over content where I think actually taking the course is necessary.

Doing the philosophy pathway in my opinion would enable me to audit both math and bio classes that I see necessary but what would show up on my transcript is just random philosophy classes. While it may sound crazy I think I am actually leaning towards doing the philosophy pathway as I have a genuine interest in philosophy and it would enable me to audit relatively more classes since I would have more free time.

Which pathway would you guys think is the most beneficial to pursue? My apologies for the long-winded post, I appreciate any help a lot!!

career • 649 views
Entering edit mode

i would go with the Math/Stats over the Bio. just the principles of genetics should be sufficient to work in the field... you can pick up bio on your own while on the job

Entering edit mode
11 months ago

In my opinion, primarily math-oriented classes like Linear Algebra would not be all that useful in a bioinformatics/programmer career.

In my experience, math classes quickly leave reality and enter theoretical realms that have very few, if any direct applications in biology.

Biology is the exact opposite of math, it is messy, and imprecise, with no strict rules, and exceptions everywhere.

I would recommend taking courses with a strong focus on applied sciences.

Look at the questions on this site, that is what "real" bioinformatics looks like, how many times was anyone stuck because their linear algebra wasn't up to snuff ...


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