How I became GrownUp Adina

This is Part I of II of a set of blogs centered on “How to become a bioinformatician”:

"”My gast was pretty well flabbered.”
- Jim Butcher in Ghost Story

This week my boss referred to me as one of a few foremost experts on metagenomic assembly. Huh? ::checks around room for the expert::

How did this happen? My boss knows A LOT of experts in the field. On top of this, this week, I’ve received a couple invitations to review bioinformatic papers and registered to lead a workshop on metagenenomic assembly at a major conference in my field. Heh? Something has been/is happening. I’m trying to come to terms with all this still and thought I’d start with reflecting on how this may have come to be…

A healthy dose of fearing failure:

My undergraduate training was in engineering, and of all things, Mechanical Engineering. I interned at engine factories and oil companies. I received my PhD in Environmental Engineering – honestly, hoping to save the environment with research that mattered. My PhD was a struggle…I had independent funding enabling some freedom in my research. This resulted in me picking such an independent research project that no one knew how to help me with it (don’t do this!). Long story short, soil proteomics is really hard, and nearly impossible without some experience or expertise around you. There was no way I was ready to lead any sort of research on my own after my PhD.

So for my postdoc, I decided to see if I could get an experienced microbiology guru to take me in. I didn’t have much going for me - he could have his pick of postdocs. I approached him to write a proposal for funding and the ONLY one I saw advertised at the time funded computational biology. I asked the guru what he thought was the most interesting science going on for environmental science, and he mentioned metagenomics integrated with environmental studies. Honestly, until the summer of 2009 when I wrote that proposal, I’d barely heard of the word - thank God for Google.

Willingness to be fearless (aka desperation for funding), followed by failure, followed by adjusting expectations:

Reading the literature at that time, I could tell that sequencing was going to be a big deal (I still think metagenomics is in its infancy). I just had no clue how to get into it…so I wrote a proposal on how I was going to just be trained in it. (I put a bit of this grant at the bottom of this blog).

Fortunately, I got the grant, and then I received data that I had literally no idea what to do with. I sank into a bit of an academic depression. I spent two weeks just hating on my MacBook alone. I picked up tons of books and resources on how to program and couldn’t get past the first few chapters. For example, I couldn’t figure out where the command line was for a long time. I just went from doing enough research for a PhD to accomplishing (in my mind) absolutely nothing for the next six months. I wanted to go back to the lab and do experiments – I missed troubleshooting PCRs, that’s how bad it was. No one seemed to care that I wasn’t doing anything, and I feared that I would never ever get a job after failing at this one, let alone save the environment.

In hindsight, there were several things going on at this time that I didn’t appreciate:

  • My advisors (both the famous one and the up-and-coming one) were giving me space to learn. They weren’t ignoring me because I was failing, they were giving me time to adjust without expectations from them. If you’re going to switch fields, this kind of support (even if not vocalized) is invaluable.

  • My frustrations were actually small victories – one’s that you have to get through to get to the next step. When I run, I’d rather hit a big climb at the beginning if you can assure me the rest of the way is flat. That is what my experience with bioinformatics has been. When I teach others, its amazing to see how frustrated they are at the beginning despite accomplishing a lot in a short amount of time. Bioinformatics is NOT like surfing the internet. Expectations have to be adjusted, its incremental successes just like troubleshooting PCRs….but A LOT better!

Really Enjoying Instant Gratification:

Once I got programming, I really enjoyed being able to see a happy result within minutes. Being a microbiologist, I was often limited to trusting that there was something in my tube even though I couldn’t see it. It drove me nuts. I really enjoy being in control of everything in computer-space.

“Don’t Stop Believing…”:

In the fact that science can actually help people. I make an effort to be able to talk about what I do and why I do it to people who aren’t scientists as much as possible. It’s important, that’s why I’m doing it! A couple of years ago, this involved troubleshooting simple code that I can now write lickity-split, but no one else in my lab knew how to do this. If I didn’t do it, it wouldn’t get done.

This all evolved into me being involved in several efforts which have culminated in my current interests and “expertise.” When I took my current job, I emphatically told my boss that I was not a trained programmer, maybe not even a good one. But I had a good track record of trying, learning, and extending…which I hope I continue to do.


I just got damn lucky with tons of resources to succeed. The most important was incredible mentorship. I also had a great team of young researchers to work with. I remember meeting one over Christmas break to go over Python Loops in his dorm. He doesn’t know this but I was really about to give up on programming that week and ask to go back to the bench. He most likely saved tons of strains from contamination in the lab :) Not everyone has these resources, but there are a TON out there that are freely available to help YOU. There is also strong community to help scientist infiltrate bioinformatics. I’m going to spend the next blog going over some of these resources and some specific advice on first steps from my experience.

Snippet of my NSF Postdoc Fellowship in Computational Biology:

By working in a top-tier research institution under the tutelage of renowned experts in the fields of microbial ecology and computational science, the following training objectives will be completed during the course of this fellowship:

(1) Demonstrate a mastery of tools and techniques to identify and evaluate metagenomic information from complex environmental samples (2) Develop the computational expertise and bioinformatics tool set necessary to: collect and organize expansive metagenomic datasets; integrate existing and novel assembly, gene prediction, and annotation tools into new metagenomic analysis software; and create user-friendly data exploration and visualization tools that streamline analysis and comparison of complex datasets (3) Gain an understanding of the state of the field and knowledge gaps of understanding community functions in environmental samples (4) Extend previous research experiences into the management of an independent research project centered around applied problem solving and the integration of interdisciplinary expertises and tools (5) Foster leadership skills through the mentorship and direction of graduate and undergraduate students

Throughout my academic career, I have intentionally developed a broad base of skills and experiences in a variety of disciplines which have highlighted the synergies of an interdisciplinary approach to effective problem solving. Through continued collaborative interdisciplinary studies, this research project will provide me with the tools and expertise to obtain my career objective of obtaining a tenured faculty position at a top-tiered academic teaching institution conducting research on understanding community functions in the environment. Upon completion of this fellowship, I will be in a unique position to excel in this area of study owing to my experiences in studying the metagenome, transcriptome, and proteome of microbial communities in environmental samples. Additionally, I will be able to recognize the potential for further advances in my field by leveraging my knowledge of biology, computational science, and engineering. Furthermore, recognizing the value of involving other skilled researchers to solve large-scale problems, my research and training objectives for this fellowship will include my direct involvement a variety of interdisciplinary networks. Developing these scientific relationships will better enable interdisciplinary collaborations in the future. Finally, my varied research experiences will enable me to relate to and communicate with my future students.

I have to thank the NSF. It apparently worked.

blog comments powered by Disqus