Career Plan: Be A Dual Benchworker And Bioinformatician

Question

[michealsmith]

This may be a topics about career plan. What about be a dual benchworker and bioinformatician at the same time?

I've been analyzing NGS data (mostly genomic data) for a year and half, either exome or whole-genome sequencing data for disease samples in order to find potential pathogenic variants. I came up with several candidate genes, and would like to do some genetic screening myself, which means go back to benchwork.

I think it's interesting to try some simple experiment say PCR, or variants validation. And I'm also recently enthusiastic about sequencing technology itself, for example, target resequencing. My interest lies in genomics, and it'll be terrific that I can be familiar with sequencing technology (say, construct library for sequencing by myself) and consequently analyze the data using computational tools, which will facilitate my understanding on genome biology as well as bioinformatics. And on top of genomics, biology knowledge on certain diseases (say those neurological disorder) is also strongly needed to guide our genomics/bioinformatics pipeline, after all, our purpose is to find therapeutics for diseases.

Of course it'll require hardwork and strong commitment, but in order to pursue a faculty position or build up career in academia, it's beneficial to do so? (Just look at those faculites, they need to constantly learn lots of new stuff to keep up, so in my eyes, our field is more like a truly interdisciplinary world requiring various skills ) But one's energy is limited, does dual work mean one may know both sides in an average level but cannot be truly professional/expert in either one? Will dual work give me an advantage or improve one's competitiveness in job market?

=================================================== Back to this question, I would say, it's quite hard. I wouldn't recommend people to work both unless you aim for becoming faculty. Personally I'm not good at handling multiple stuff simultaneously. I could only focus on data or bench.

Answer 1

[Josh Herr]

I think a lot of what tools you need and/or should develop depend largely on the questions you want to ask in your research.

I started wet lab work 20 years ago during my undergraduate research, but the lab techniques and technology have changed drastically in that amount of time. I've moved to a more computationally focused side to deal with more data derived from newly developed lab technologies. Someone else may come from the computational side of a question and want to learn to address these questions using wet lab techniques.

I think there is the potential to suffer from "jack of all trades, master of none"; but having knowledge in different areas is not going to hurt you. I would focus on understanding your weaknesses and working with them while continuing to build up your strengths even more.

Your development also largely depends on your career goals: My PI does no wet lab or computational work, but he understands both very well and pays to maintain both a wet laboratory and server & office of bioinformaticians. Basically he is constantly writing and managing personel, so if your intent is to be a PI, perhaps you should really be developing your writing, management, and budget making skills.

[Istvan Albert]

this is a good point that I forgot to make - being in academia as PI primarily means people management and getting people do the research you would rather do :-)

Answer 2

[Damian Kao]

It's not easy to do both. I thought I could do it when I started my PhD. I went into my PhD with 2-3 years of benchwork experience and some web development experience. I am now pretty much only a computational biologist after 3 years. I found it difficult to switch modes and eventually just found benchwork to be too tedious for me. However, I found having the benchwork knowledge to be useful in interpreting your data.

My advice, if you really want to attempt it, is to try not to do both concurrently. Maybe focus on benchwork to generate your data for the first couple years, and then focus on analyzing the data afterwards.

Answer 3

[Istvan Albert]

I think having the option to switch domain is a great opportunity to deepen your understanding - viewing the problem from a completely different perspective can be refreshing as well as exceedingly valuable.

Understanding multiple facets of data production and analysis can make you one of the best prepared individuals in the field - and not just from the academic perspective.

Answer 4

[tiago211287]

I did my master's degree in Biochemistry but my project was practically 75% bioinformatics and 25% benchwork. I started from zero bioinformatics knowledge, but in undergrad I had great benchwork experience like cell culture, cloning, rt-pcr, q-pcr, ELISA, mouse infection, treatment, etc. Then I thought in moving to Bioinformatics department in my PhD because, doing bioinformatics while staying in the biochemistry department was making me learn none right.

Now that I am learning much faster bioinformatics than when I started my project. I am thinking in do both at the same time. I must come back to bench and take tiime to validate my findings. I think would be great if I could conciliate and be A dual benchworker And bioinformatician.