Forum:Looking for advice on making a grad school decision on bioinformatics/computational biology programs
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5.2 years ago
JQX ▴ 10

Hello bioinformatics/computational biology specialists,

I am looking for your advice on making a grad school decision on bioinformatics/computational biology programs.

I got accepted to the CMU Computational Biology program (a joint CMU-Pitt Ph.D. program) and the UCSD Bioinformatics & Systems Biology Ph.D. program. I have to make the decision very soon.

I am wondering how these two programs compare with each other regarding the program strengths, career prospects, etc.?

Which program would you recommend?

I'd greatly appreciate your advice.

Thank you very much in advance!

graduate program bioinformatics computational bio Forum • 2.3k views
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5.2 years ago
cbio ▴ 450

I'll be starting my first rotation at UCSD as part of the BISB program in June. So i'll recommend that program! :P

It really depends on what type of research you are interested in.

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Thank you very much for your recommendation!

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5.2 years ago
Rob 5.2k

What type of work are you interested in? I spent a few years (as a postdoc) in the Comp Bio department at CMU (in Carl Kingsford's group). It's a fantastic department with (obviously) some really strong faculty and students.

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Thank you so much for your advice! Your information is really helpful!

The program at CMU is Computational Biology (rather than Bioinformatics). I guess there is a vague boundary between Computational Biology and Bioinformatics. I am just wondering if the CMU Computational Biology program has a bit different focus? I’d appreciate your advice on this aspect.

Another thing I’d appreciate your opinion on is: for the research area of computational genomics, do you think there are many work remaining to be done in this area? Or is the area getting slightly mature? What about systems biology and computer-aided drug design?

Thank you very much for your advice and for sharing your experience with us!

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When I teach my grad class "Introduction to Computational Biology" (which is in our CS department), I actually try to de-emphasize the vague boundary between comp bio and bioinformatics. While many people, when asked, will define these slightly differently, I don't find there are useful canonical definitions that are distinct enough to try and draw a "boundary". Anyway, the CMU Comp Bio program does have, as part of the program requirements, a lab course and some more "biological-y" course requirements. I'm not sure how this compares to the UCSD program, but in this case the CMU program really is a mix of Computer Science and (mostly molecular) Biology.

Regarding your second question --- I absolutely think that computational genomics is a ripe area for research. While it's true that a lot of great work has been done in this area, and that we have some pretty amazing tools (from the algorithm & data structure side) for certain problems, the vast majority of interesting problems are far from solved. For example, the popularization of long read technology is making many old problems new again, and we're in a phase where we're still working on solving certain basic problems in the face of new technologies with new characteristics. Further, as I tell my students, there are problems for which, though we have "production ready" tools, substantial fundamental improvements in methodology are still to be made (e.g., both genome-guided and _de novo_ transcript assembly come to mind). On top of this, there are newer types of experimental assays (e.g., 3C, 4C, 5C, Hi-C) that raise new computational challenges and require new methods and algorithms. I wouldn't worry about computational genomics being too "mature".

Systems biology is also still a wide-open research area, with a lot of challenges, both small and large-scale, and a lot of fundamentally difficult problems (i.e. things that may likely require completely new methodology to address adequately). Systems biology has also matured considerably over the past decade in terms of the volume and quality of the data to which we have access. It's a promising area for research if you can find a problem where you think you might be able to contribute. I can't say much about computer-aided drug design, so I'll just mention that I know a lot of smart people working on it, so there must be some interesting and challenging problems there, though I've not had the chance to learn much about them yet.

Good luck with your decision!

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Thank you so much for your very thorough advice!

Your view and analysis about the field really help!

Thank you very much and I greatly appreciate it!

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