Undergrad research in Computational biology
wet lab like actual experiments are getting more experience


It is a common misconception that biology almost always happens in a wet lab. Indeed, some things can only be done in a wet lab, but computational biology is actually one of the greatest examples that counters this misconception, due to its flexibility.

If you want to spend more time behind a pipette instead of a keyboard, you should be able to ask your research advisor for projects or classes that get you more involved in that direction, for example PCR and gene sequencing. However, if you believe that computational biology is "less experience" than wet lab biology, it is important to understand the benefits that dry computational biology brings to general biological sciences.

Take Mendel's cross-pollinating peas exercise. If done in the real world, it would take several weeks to generate a single generation of peas (and hope that nothing bad happens that causes them to die). With the power of computational biology and some programming, you can perform dozens or even hundreds of generations' worth of experiments in a single day.

The power of computational biology comes from the fact that it can be done either cooperatively or independently of a wet lab. If you only want to do data analysis, you can do that. If you want to apply some real-world wet lab culturing with image-based analysis of PCR scans, you can do that.

As a computational biology student, you should be able to determine as much or as little wet biology or computer science that you want to do. My thesis was entirely done without ever seeing a biological organism, as I only used neural networks to simulate generational development.