My day usually begins the same way most office jobs start. That is by answering various emails from coworkers and clients. But after that, it gets very scientific. Kimera Labs manufactures exosomes, which are nano-scale extracellular vesicles – very small packages of signaling information one thousandth the size of a cell. They are produced by virtually every cell type as a means of intercellular communication. This natural paracrine signaling system allows a healthy body to run like a well-oiled machine. Part of my job entails RNA sequencing, so after replying to emails, I often begin my day by running a new sequencing or checking on the previous run. We are studying the ways different genes express themselves, hoping to find new and interesting gene expressions that might be useful in treating disease or generating tissue. So, a lot of my day is spent processing raw sequencing data using different software and databases. That also entails writing scripts to do specific analysis tasks. After that, it boils down to preparing the various analysis results for presentation or discussion among my colleagues and peers. I also spend a lot of time reading academic papers and developing or optimizing the analysis pipeline.

I spend about 50% of my time developing or optimizing the analysis pipeline and maybe 30% of my time preparing for the next sequencing run and prepping analysis results for presentation, 10% of my time doing research, and another 10% reading papers

Pros: Well, the pros are it’s a highly paid job that allows me the privilege of doing what I love while benefiting all mankind. Still, you must be equipped with multiple skillsets and a broad array of knowledge and aptitude in biology and computer science. Knowing Python and R is a must.

Cons: The biggest con is that you need a very long period of education and training and lifelong learning is required to keep up with new developments in bioinformatics and biology. The job requires extensive knowledge, skills, and experience.

Dr. Jianjun Shi, PhD
Kimera Labs, one of the nation’s top manufacturers of placental MSC (pMSC) derived exosomes.

My work life as a doctor-researcher-bioinformatician is always an adventure and rarely predictable; if there’s one thing I can say for certain, it’s that it always keeps me on my toes! I completed a joint MD/PhD degree at Harvard Medical School and MIT under a fellowship by the NIH MSTP (Medical Scientist Training Program) which is essentially a long-winded way of saying that I balance responsibilities as a physician (or clinical consultant), medical researcher, analyst, and technical writer in proportions that vary day-by-day, week-by-week.

My work schedule is essentially task-focused, and I’ll be recruited for projects depending on prioritization in a way that makes use of my unusual interdisciplinary skillset. Thus I might be called upon for medical consultation one week when that’s mission-critical (for example in the context of treating rare diseases, for which I did my specialist training or pandemic preparation). Then in another week, I’ll pivot into research opportunities in drug development when my expertise in gene therapy or computational biology can lend a hand. Or I might be knee-deep in bioinformatics analysis when my skills and talents in machine learning or advanced scientific programming can be instrumental in processing a new ocean of data pouring in. That’s simply “the world of the physician-scientist,” as my mentors at Harvard Med dubbed it when I was selected for the dual-doctoral degree track and scholarship.

Pros

I’d say the most significant of the pros for this sort of work life are indicated in the very text above — it’s constantly interesting and intriguing, and there’s an ongoing opportunity to have a major impact in the ideas we can translate into action. That’s particularly so in the protean, fluid realm of “translational medicine,” which describes one of our primary roles: translating promising, often discursive basic research into tangible systems and products that enhance human health. In part because of the multi-disciplinary nature of an MD/PhD, one of my key mentors in med school gave advice to my colleagues and me that our guiding principle should be to start each day, week, and month with a simple question: “Where can I apply my mix of skills to make the most difference?” We’re spurred to be ambitious, entrepreneurial, and even to leap onto moonshot projects when they spring up; our weird and wonderful skill set puts us in a position to push envelopes, and be innovative and disruptive in a way that will have world-altering contributions. As a bonus, I’m also able to meet and work with some of the coolest, most talented people in the world in many walks of life. In part thanks to these connections and their encouragement of my own creative side, I’m also a popular professional musician (founder of the alt-rock band Kant’s Konundrum) and published novelist.

Cons

And the cons? Among the downsides, this sort of work life and lifestyle can be unpredictable, exhausting, and grueling at times — the flip side of the very coin that makes it so rich with intrigue and novelty. As my girlfriend has dryly noted, when planning out our schedules for the weeks and months ahead, she might as well pin my calendar to a board and toss random darts to figure out where or when I’ll be at any given point. This naturally can make things tough for relationships and a social life in general. It can also be hazardous, depending on what I’m specifically doing. I’ve contracted some devastating respiratory conditions while working as a physician that entailed an arduous recovery, and I’m constantly at risk of such dangers given that part of my job involves being on the frontlines of discovery, surveillance, and treatment of human disease, with all the uncertainties that entails. It’s a balancing act, like so many other things in the world, and sometimes things fall out of balance with so many moving parts. But the novelty and constant prospect for discovery ensure there’s never a dull moment.

J. Wes Ulm, MD, PhD
A Hustler’s Tale

Get up. Pour the first of the day’s many cups of coffee. Sit down at my desk. Stare at the bug that I gave up working on at 2:00 AM the night before. Realize the bug hasn’t fixed itself. Mumble angrily. Pour another cup of coffee …

Okay, not all the time. Honestly, I can’t say what a typical bioinformatics working day is like because my job is somewhat unusual, in that I’m the only bioinformaticist in my group (a physiology lab) and I work at home most of the time, which has its good and bad points. See “2:00 AM” above. But the tasks that take up most of my time, in rough order from most to least, are:

1. Coding. There’s a lot more to bioinformatics than programming, but programming is where I spend most of my time. About a quarter of the coding time is spent actually implementing new algorithms and statistical tests. The rest is mostly generating customized reports.
2. Math. Biologists want answers to questions, usually yes-or-no. My job as a statistician is to answer those questions and convey an idea of how uncertain we should be about the answers. Probably 90% of the time, I can do that very quickly, with some standard testing procedure. The other 10%, I have to devise new procedures that are defensible and produce interpretable results. This doesn’t mean re-inventing the standard tests—other people have already done that work, and it would be a mistake to try to beat them—but it does mean dealing with a lot of multiple comparisons and conditional probabilities that require using existing tests in creative ways.
3. Learning and annotating the data. This takes place almost entirely at the start of a project; it’s very time-consuming at that point, but after that, I know the data set like an old friend and it shouldn’t be necessary to go back to it. If I do have to go back—which I sometimes do, more often than I’d like—that means I didn’t drill into it as thoroughly as I should have the first time around.
4. Writing. This includes both internal documentation (everything I do in items 1–3 needs to be written down in a way that will make sense not only to me but to anyone else who needs to read it in case I get hit by a bus tomorrow) and preparing papers and conference presentations. Sometimes this goes very smoothly, other times it’s an exercise in pain.
5. Studying biology. My wet-lab co-workers try to explain everything I need to know about what we’re working on, and they do a pretty good job. But I still need to download bio papers and crack open textbooks and read about the subject until I understand it. That’s the only way I’ll know if the answers I’m giving them make any sense.
6. Meetings. A good lab meeting—yes, they exist!—is a chance for everyone in the lab to give a summary of what they’ve been working on and ask each other questions. It’s very easy for people to get focused on their own little niches and lose track of how their work keeps the lab moving forward. Throwing ideas back and forth in person is the best way to ameliorate that problem.
7. Studying bioinformatics. Just because this is what I do for a living doesn’t mean I know everything I need to know. Reading papers and attending seminars helps me stay current.

At the start of a project, 2 and 3 are what I spend most of my time on. Once things get rolling, 1 and 4 are daily, with 2 usually coming up a couple of times a week. 5, 6, and 7 are weekly to monthly. I try to take some time out every day for sufficient sleep, nutrition, exercise, and relaxation too. Some days that happens, some it doesn’t.

I work for a major biotech as a bioinformatics scientist and all of my academic credentials are in bioinformatics. However, I’m trying to move from bioinformatics to web companies. I’d like to do this for one reason and one reason only–web companies pay 50%-60% more than biotech does. I have co-workers who have already made the switch so I can confirm this to be a known fact in my professional circle.

I don’t know exactly why this is the case, but I think it’s because the alternative for us bioinformatics scientists is working in academia (which as we all know, pays peanuts). However, the alternative for working at a web company is working for ANOTHER web company–so the salaries are MUCH more competitive. Since the market seems to work this way, it seems like it’s really up to the graduate students and research faculty at major universities to work on these difficult biological problems and progress the field forward.

To be sincere some bioinformatics jobs are like any other programming for enterprise jobs. They will give you good enough requirements and have to write a program or module following those requirements, but you’ll be a programmer coding software more than a scientist as you won’t be required to know beyond the minimum of the bio-problem being solved nor performing scientific methodology, paper review or experimental design which are the researcher duties.

On the other hand, if you really mean bioinformatics scientist, you’ll need good domain knowledge and perform all the above tasks. If that is the case I can say that I find it very interesting as you not only apply the scientific skills/tasks but also create tools to solve the problems you or your group is studying. Still, this depends on you, your group, and the problem being solved. If you don’t find the problem interesting or important enough and the environment encouraging, no matter how much bioinformatician or scientist you are, you probably won’t be happy. But if you do, well, it can be very nice.