Forum:Is there anyone who was a pure biologist?
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7.0 years ago
Chong Tang ▴ 100

Is there anyone who was a pure biologist?

I'm preparing to transform from a wet-lab based pure biologist to a bioinformatician. To be honest, I haven't use any statistical methods for years. So learning math and statics made me really tired at the beginning.

And I'm still wondering if it's worth to do so to transform from a bench-working biologist to a bio-info -programmer. Especially, I have already had 6 years experiences with wet-lab. Am I just going to decard my past six years experiences?

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"Am I just going to decard my past six years experiences ?" "Here Is Something False: You Only Live Once": http://www.smbc-comics.com/?id=2722. :-)

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I did wet lab work for 30 years, for the last 5 have done mostly informatics. The biology background does help out occasionally. I find programming to be a bit more rewarding than wet lab experiments on a day to day basis, you don't seem to hit walls as often. (Except when stuff won't install and you can't figure out why - arrgh).

I do make my own sequencing libraries to get a little lab fix and save some cash

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How can you have not used statistical methods for years? When I was bench, it was essential

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Who says computational biologists are any more or less 'pure' that wet-lab or field biologists?

(I understand what you mean, but don't think you are becoming less of a biologists if you take up a computational position)

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7.0 years ago
Neilfws 49k

I assume by "pure biologist", you mean "has trained, qualified and worked in a biological science."

My qualifications are in biochemistry and I was a wet-lab biologist (molecular microbiology), including my PhD years, for about 8 years before transitioning to computational biology & bioinformatics. At that time, most bioinformaticians were self-taught "ex-wet-lab" scientists, since there were no university programs in the subject.

My personal bias is that the "bio" in "bioinformatics" is at least as important as the "informatics". Training in biology will be beneficial, not least in enabling you to communicate with the wet-lab people. They often assume that conversations with computational biologists have to begin with "what is DNA"; things move a lot quicker when you convince them that this is not necessary.

There are always transferable skills and experiences when we transition through our working lives. No previous period is a waste or an irrelevance.

Having said all that: you don't sound especially enthusiastic at the prospect from your question, so maybe you need to figure out if the transition is what you actually want to do.

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And four years later, I followed you on GitHub. Thanks for such a sage reply!

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7.0 years ago

Hi.

I think there are quite few "pure biologist" that turned to the darks side of bioinformatics, and I am one of them. I didn't have any formal training in programming/informatics till the end of my Ph.D. in molecular biology. For sure, all you knowledge in biology is not wasted. It is an asset.

However, do not underestimate what is ahead of you. You'll need to be able to write scripts and programs on a daily basis on real problems and practice, practise, practise. It is not something you can study from a book before going to bed. Nor something you can do a day or two a month. You'll need a job that allows you to invest time in learning. If you have a group of bioinformaticians you can ask for guidance or advice, that would speed up your learning. Also, you should really ENJOY it, or it will be very hard, frustrating and boring.

It can be very fulfilling and you can start to do things you couldn't do before, so might be very productive. At the same time, you'll be tempted to solve many of your problem using tools you already know (like Excel) and it will take you very long to do something very simple

Depending on your needs, you'll need to know your way around a unix/linux system a scripting language (Perl - Python), and I would say R to plot and play with numbers. look here for what is common in this community. Again, if you have somebody with expertise around, start using what they use.

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Hey Stefano,

I'm in my last year of PhD (moleular biology) and leaning towards bioinformatics. I was wondering if your thesis revolved around "pure biology" or were you able to mix a bit of bioinformatics in that?

Thanks

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7.0 years ago
Katie D'Aco ★ 1.0k

I don't think your pure biology experience will go to waste if you transition to bioinformatics. You will have valuable biological insight to the algorithms and results that many others in the field don't have.

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7.0 years ago

Do you have some previous computer skills? That would help tremendously. I did a genetics degree during undergrad and was a lab tech for 2-3 years before I started my phd. I was planning to do a wet-lab based phd until I was given the opportunity to work on data. I had some programming experience previously so I was able to adapt. I can imagine that it would be a lot harder if you had zero computer skills. There will probably be a steep initial learning hump. But once you get over that hump, I think you'll be fine.

I don't see this transition as a waste of my wet-lab experience. I find the wet-lab experience gave me a more realistic perspective on how I interpret the data.

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7.0 years ago

Former molecular biologist here. We're pretty common really.

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7.0 years ago
Brett ▴ 150

Any good bioinformatics team, has a range of people with a range of skills. Often you will get pure coders who know nothing about biology, who are greatly assisted by people like you who act as an interface to the real world.

Personally I was very much a biologist (in academia), who did bioinformatics 10 years ago and has had to revisit those skills as it became my main line of work (in industry). Whilst there are 101 biochemists that could do my job, but there are very few bioinformaticians, so I would strongly recommend making the jump.

None of your background needs to be wasted as the bioinformatics field is so wide. No one is an expert on all aspects of bioinformatics, but with your previous knowledge you can become an expect in certain aspects of the field. Even "simple" things like a BLAST search and phylogenetics. Many scientists can do those things, but very few actually fully understand the limits of the data, or how to get the best result (its typically a black box). Just a bit of bioinformatics knowledge can go a long way to improving your job prospects.

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7.0 years ago

I am not a pure biologist, but I interact with many microbiologists who have the same reservations as you do when confronted with bioinformatics or stats. Do not fret, take baby steps, iteratively improve yourself, and you'll do just fine! Trust me on this :) Nothing goes to waste really! Eventually all the dots connect together. Persevere! and read this book:

"The key to success in any field is, to a large extent, a matter of practicing a specific task for a total of around 10,000 hours" Outliers

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6.3 years ago
Biomonster ▴ 30

Hi, there!

I also am a PhD student in biology (molecular biology) and interested in switching to bioinformatics. You should never regret your past experiences that in fact made you who you are now and opened your mind to consider other opportunities for your career. My situation is very similar to yours and I struggle to identify the steps I have to make to become at least a rookie in bioinformatics, but like others said, you need to get involved in bioinformatics-related projects in order for you to experience the real deal.

I'm interested how do you see bioinfo now, after 8 months since your first post.

Hope for the best!

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6.1 years ago
mxs ▴ 530

I guess I can add something. I am (was) a biologist. I did my graduate studies in biology and then phd also in biology (tried to make a switch, but could not find the money). However, for 7 years I haven't done any biology whatsoever. Today I consider myself a CS programmer (c,c++,Perl,R,...) well versed in all three programming styles (procedural, OO and generic). Also, I work as a linux system administrator and a bioinfo "consultant" for small biology groups. But my true interest lies in systemic problems associated to computational complexity and approximation algorithms.

The reason I "turned" was the money. Yes, extremely noble reason. During my studies I figured I could earn some extra cash by doing some programming (first for my friends and then for small bio groups). After a while I found the beauty in slowing problems rather than capitalizing on their end results. Moreover, I think this is ( my personal opinion ) the biggest difference between analytical areas like biology, computational biology and (hard-core) bioinformatics (including areas of computer science and mathematics). While in the former you are putting the emphasis in questions like WHY?? in the latter you are interested in HOW?? (both EQUALLY IMPORTANT!)

I must admit, that making a switch was and still is hard. While biology community looks at you as an outcast, computer scientists don't take you seriously enough. As a result you end up mostly doing freelance-jobs (though I still have a regular job, at least for a year). Switch is not "cheep". You need to invest a lot of time and effort into it if you want to produce competitive solutions and during that time you cannot capitalize on your work (publish papers: since today this is apparently the only measure of accomplishments worthy of career progress in academia (sorry for sounding a little bit frustrated here)), which puts you well behind your peers.

So regarding the question: "Is it worth?" I would say that depends how far are you willing to go. If you decide to stop on analytical fields of computational biology I would definitely recommend it. It will reduce your dependency on others and give you a career push, but be careful, control your curiosity and remember: "curiosity killed the cat" (I realize this is non-scientific but what I am trying to say is that it is important to keep the balance - this is the way of evolution otherwise you might find yourself under a purifying selection)

mxs

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It's a shame that people who decide to leave academia are seen as "selling out". I really dislike this attitude in academia where sacrificing personal/financial freedom in pursuit of science is put on a pedestal and is an expected career path. When have we become monks?

While I appreciate the passion that some people have for their work, I find that it is hard to reconcile this passion with the tempered, logical mind you are supposed to have as a scientist. Obviously they are not mutually exclusive traits as you can be a good methodical scientist and still be passionate about your subject of interest. But I would rather the trait of being a good scientist be associated with being methodical and logical rather than being passionate.

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6.1 years ago
alexcd201403 ▴ 30

well, how about your bioinformatician friends? you can ask some ideas about them. how they think about their work, they might help you. 

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20 months ago

Before entering bioinformatics, I worked as:

  • Laboratory Technician in Dublin City Council (Ireland), testing wastewater, river, and lake samples for contamination as part of national and EU regulatory monitoring
  • Shellfish Microbiologist at Marine Institute Ireland, same as above but via shellfish (and on opposite coast from Dublin)
  • Laboratory Assistant at University of York (UK), working in quantum chemistry... basically, smashing sugar molecules together to study their components
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6.1 years ago
Mohamed ▴ 70

I think whatever you learn in bioinformatics, you will still be not a real competitor like pure mathematician/programmer/statistician. This, again as I think, part of the deceive that biologists think by learning some bioinformatics. I am also coming from biochemistry field and I might be mistaken but learning bioinformatics is only to add more to your CV. Unless you completely switch to bioinformatics field and start like undergraduate student. I really wonder and wish to know is there a real example of someone biologists who become successful and completely independent when turned to bioinformatics (I guess the answer is no, the successful example is someone biologist who knows the rules but control other real programmer who do the real job for him).

Anyway, always look for the best thing to improve your income. Doing bioinformatics is a plus (but again, I mean mastering how to use a software NOT to invent a software)

Mohamed

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If you scroll up, you'll see that there are many of us who were pure biologists and are now bioinformaticians. By your argument, someone with a math/stats or CS background could never be a real competitor since they'd need to go back to being an undergrad to learn enough biology to have a clue. There are reasons that modern science is increasingly a team activity.

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Yes I also disagree with this. The term bioiformatics includes 'bio' for something and as a pure-biologist jumping into bioinformatics is an advantage against pure mathematicians/statiticians/computer_scientist. Usually the field is open for any one of those 4 cathegories to jump in because as it has been pointed out above a good team of BI should have people with a variety of skills. As good as you can be programming, when you perform BI analysis, if you do not have a background in biology you will not be able to interpret results, specially when it comes to understanding biochemical pathways and genetic regulation just to mention some examples. If you can create a new model or write a new script that's great and probably a mathematician or a computer scientist will need 10 times less than you but that' the end of what they can do usually, in your case as a pure-biologist, you will struggle to write a program, you will struggle to have a software run, or to do some statistical analysis, but once you've concluded, you will look at your data and know what you have between your hands, you will know what to do from there, what time of hypothesis you want to resolve based on your results, that is an asset for a BI. I have seen myself mathematicians modelling parameters with absolutely no biological sense just because they could not understand the physiology behind the function.

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