Forum:Should I Pursue A Bioinformatics Msc?

Question

[biostepho]

Hello everyone

I'm a life sciences undergraduate student and I reached the moment in which I have to decide in which way continue my studies.

I enjoyed much my internship in the laboratory but I always had the feeling that I didn't had the theoretical/practical means to have a good interpretation of my experiments. Another point in favour of pursuing this path is that I'd like to have a more integrated view of biology (and address my studies in such a way), maybe in despite of a more detailed and defined one.

I was wondering about enrolling in a Bioinformatics MSc and I'd like to have some tips if it's the right choice for me. The questions are:

Would I stop definitely working in the lab? Bioinformaticians do run their own experiments or they spend all of their time working on the computer, analyzing other scientists' data?

What are the prospects (scientific challenges and work possibilities) in the future for a student choosing to study bioinformatics now? Wouldn't I risk to become an useless "hybrid"?

Thank you for your attention, I hope someone could help me to clear my mind about these themes.

Cheers
Stefano

[Casey Bergman]

You might want to look at the reasons for doing post-grad work in bioinformatics in this post: Top N Reasons To Do A Ph.D. or Post-Doc in Bioinformatics/Computational Biology

[biostepho]

Thank you, very enlightening post. I assume the facts pointed out can be referred also to an earlier training as a MSc.

[Josh Herr]

That is a great great blog post. Gonna pass that one on!

[Josh Herr]

Questions like these come up quite frequently, so you'll find some good information in past questions and forums. In addition to the link Casey posted, here are two more posts ( A: Getting Experience in Bioinformatics and A: Career plan: be a dual benchworker and bioinformatician ) from the last two weeks with some similarity to your questions.

[biostepho]

I'm sorry I did not search for older questions as this one (didn't find any at first look), thank you for the kind answer

Answer 1

[Philipp Bayer]

I'm a PhD-student in the beginning of my second year, here are my answers to some of your questions from my (limited) point of view.

First of all:

Another point in favour of pursuing this path is that I'd like to have a more integrated view of biology (and adress my studies in such a way), maybe in despite of a more detailed and defined one.

Now that I'm working in bioinformatics I feel that I easily start to drift into a very "un-integrated", highly specialized view of biology - that is, no biology at all! I easily focus completely on algorithms, on how to clean data, on how to get it to play along nicely, on finding a pretty way to plot certain behaviour! That comes back to bite me when I do talks or have meetings about my results, I easily "forget the biology behind it all", as my advisors say. That is something you should keep in mind if you focus on this career!

Would I stop definetely working in the lab? Bioinformaticians do run their own esperiments or they spend all of their time working on the computer, analizying other scientists datas?

Most bioinformatics researchers I know do not work in the lab at all. Why would you? All that pesky security-training, just to stand around dangerous chemicals and perform the same movement 500 times, as a bioinformatician you can have a nice hot cup of coffee and a cozy chair!

About other people's data: Yes, you analyze their data, or how I like to see it: I tell them using their "old" data which new data to generate and then I have a look at it. This way I don't have to sequence stuff in the lab but still get the benefits. I definitely run my own experiments: for example, we have mountains of genomic reads that were used in assembling genomes, but you can do so much more with! (call SNPs, call indels, do maybe even population studies...) The few computational biologists I know work with theoretical models so they don't need other peoples' data.

What are the prospects (scientific challenges and work possibilities) in the future for a student choosing to study bioinformatics now? Wouldn't I risk to become an useless "hybrid"?

I have no idea. I do know that getting a job in the field right now is much, much easier than, say, as an ecology PhD. All the former PhDs I know in my lab got a job offer during the second year and were never unemployed.

It's hard to tell what the scientific challenges are going to be - right now, bioinformatics as a field is struggling with reproducibility of studies, as most published papers don't really include the necessary details you need to reproduce them. The discussion is ongoing and will probably lead to a slightly different model of publishing, i.e., more focus on arXiv, more open data like with GigaScience, journals that force you to publish your code with your paper, more open-ness in general, maybe even forced tests (Haha as if)?

The specific challenges per sub-field are diverse, what do you want to focus on? If you focus on plant-genomics (my field), we still don't have assembly-algorithms that properly handle polyploidy, or whole genome duplication-events; if you focus on genome assembly, the next generation of sequencing machines will have a much, much longer read-length, and none of the current algorithms really use that information (maybe ALLPATHS?). Plus PacBio-reads seem to be dirty all over the reads, and the current cleaning programs are very slow (at least for my plant datasets). There are many other sub-fields like evolutionary bioinformatics, no clue what the problems there are.

[Mateusz]

Very nice and valuable answer, however I need to disagree with one point. I am also bioinformatician (PhD student) and I see biology behind my research. It's applied bioinformatics where I am not implementing 'heavy algorithms' (at least so far) but I am using accessible tools (together with Python, mostly for scripting) in order to analyze data. I don't produce data myself in the lab - since I am working on protein evolution I work on the sequences and structures. It covers homology detection, sequence properties analysis, structure modelling and so on.

It really depends what you gonna choose - either applied bioinformatics or as the author of the post - bioinformatics with strong emphasis on computer science.

Answer 2

[Ane]

you might find this article useful, too! Systems Biology and Bioinformatics: Something for Everyone

Answer 3

[Istvan Albert]

Just to answer one of your questions specifically (for the other answers read the the posts linked in the comments):

• What are the prospects (scientific challenges and work possibilities) in the future for a student choosing to study bioinformatics now?

This often comes up in various contexts so here is my opinion. The field is undergoing a radical expansion with far more jobs than qualified applicants. But one should also understand that this is not a line of work that is easy to get trained in. Furthermore the tasks that one needs to do won't be particularly easy even after you do get that training.

[biostepho]

Yes I agree it won't be an easy path (I had some basic training regarding programming and statistics, not much although..) and I know the tasks regarding bioinformatics/computational biology are not simple. I was wondering if having pursued a molecular biology degree would not be a disadvantage compared to someone pursuing a computer science degree first and then taking interest in biology, but after reading also the other posts I guess it won't be so

[Istvan Albert]

I would say that the exactly the opposite is true - someone with computer science background and no training in biology would be in a more disadvantageous position - remember all insights that one makes are in biology! The computational/algorithmic thinking also depends on a an innate ability and usually develops faster than acquiring the proper background in life sciences.

[Ben]

On my bioinformatics MSc we had both CS people and bio people; as you'd expect, CS people found biology hard and bio people found CS hard, both had significant knowledge gaps when starting. In the end your undergrad isn't that important really, the biology you'll start looking at is (sooner or later) well beyond your BSc.

Answer 4

[KCC]

I have only been working in bioinformatics for a year and a half. So, grain of salt ...

I have found it much more common that a bioinformatician or biostatistician works closely with an experimentalist. I think one reason for this is wet-work and bioinformatics are both full jobs, that require full-time attention to be done right.

Bioinformatics is complicated. One needs to learn statistics, both frequentist and bayesian, since people use both; mathematics to get through the advanced probability theory, statistics and more exotic tools like Fourier series; computer science for the algorithms; programming for the implementations, usually multiple programming languages, such as C, R, python and perl; and tons of software packages, not only how to use them, but how to navigate their idiosyncrasies. Even figuring out how to get the software to run on your computer can be a chore. I find that I am constantly having to switch between Unix, OS X and Windows. For instance, a version of the software you are using might be available in one OS, but not the other. I also have to spend time learning about the local computer network (how to submit jobs to the queuing system etc). I think probably a lot of people have that issue and the rules and software change from network to network. Finally, one needs to know biology which tends to involve hours of reading. Besides this, at least in my work, it is quite helpful to know some biochemistry. I know others who need optics. So, in general, I find I have a full time job, with lots to do; and lots that I haven't done yet.

I think if you do a MSc in Bioinformatics, assuming you do well in your courses and nothing changes about the job environment, you will probably be highly in demand as a bioinformatician, because bioinformatics is in high demand, and a bioinformatician with deep understanding of the biology is even more in demand. Biologists are less in demand. I see many of the biology graduate students leaving biology, doubtful about their job prospects.

In terms of concern about doing both lab work and mathematics with equal frequency, I can think of a few subfields. I know a few people who work in optics and they seem to use the biology, mathematics and engineering all at the same time. Take a look at work in optogenetics.

Anyway, that's my two cents.