I am a freshman and been doing Computational data analysis(using R) and map(kallisto,bowtie,.....) the data a grad student gets from sequencing. I feel like my other lab mates who are doing wet lab like actual experiments are getting more experience. I take lots of time to understand the data just to output or make a conclusion. How can i get the most out of computational aspect of the research. I enjoy what i am doing, and it is nice to come up with conclusion and professor agrees(or disagree), but i feel like i am not contributing as much as my lab mates.

I am planning to apply to grad school(computational biology, genomics). Is there any advice on how to get the most out of my undergrad experience ?

  • 1. You have 3 more years to do a wider range of stuff. 2. If you want to do computational biology, doing data analysis would seem to be an ideal gig. – Jon Custer Jan 7 at 21:49

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.

  • what skills do you think someone need as an undergrad for phD in comp bio ? – testing321abc Jan 8 at 1:53
  • @testing321abc It will likely be the same core courses that a MS in Computational Biology requires. Genetics/Dev Bio from the Bio Side, Statistics/Math from the Math Side, and Algorithms/Neural Networking from the CS side. Your graduation requirements should closely mirror what you'll need. – Compass Jan 8 at 11:25
  • Do you think double majoring in CS (focus on compution theory and algorithms) and compuitional biology (focus on genomics) would be a good combination and worth the effort ? Or can I take computer science with minor in computional biology ? I feel like double majoring might be too much – testing321abc Jan 9 at 8:22
  • That's a choice you'll likely need to discuss with your undergraduate advisor. There are very little benefits from having a second Bachelor's in CS when your primary is a hybrid Bio/CS. It won't make you stand out in future applications AFAIK because the coursework overlaps very much. – Compass Jan 9 at 14:53
  • Only 3 courses overlap. You can't double major if more than 3 overlaps, so there is a lot of courses and areas covered in one not covered in another – testing321abc Jan 9 at 20:38

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