Meet Jess Smith
Molecules Don’t Lie — If You Know How to Ask
Jess joined Fulcrum Genomics in December 2023. She has worked in immuno-oncology, antibody discovery, molecular diagnostics, and core sequencing technology improvements — where her background in physical sciences informs her consideration of the physical processes and molecular mechanisms involved in generating sequencing data. We recently sat down to chat about work and life as a bioinformatics consultant.
What’s your area of expertise, and what excites you about your work?
Jess: I’d say I’m a generalist, in terms of bioinformatics expertise. I do have more of a scientific background and training, though having been in the field for some time now you do find you pick up a lot of software engineering, and in particular cloud architecture expertise. As a generalist I like seeing how these technologies touch many different fields. Most of my jobs have allowed me to use RNA sequencing and DNA sequencing and do some assembly of constructs, and, and, and… I like that I get to see the broad impact.
In terms of what excites me, it’s the scientific problems. I think of my role as a bioinformaticist as ‘interrogating molecules’. I think part of that comes from my background in physics and chemistry. Of course we have to write good software in order to efficiently and accurately interrogate molecules, but ultimately what’s coming off a sequencer is some sort of physical signal that is correlated to a molecule. What biologists are usually interested in is what those molecules are doing in a biological sense, so providing them an accurate readout of what the molecules are doing is really the job. Really, what excited me about analysis of NGS was the massively parallel scale. To get so much information about so many molecules all at the same time! It’s really cool.
What’s a common challenge in our industry that people don’t talk about enough?
Experimental Design
In the last ten to twenty years it’s become so easy to take some DNA or RNA and just throw it on a sequencer, see what happens. Doing good old-fashioned hypothesis-based research is what’s going to get you the answers you want, more than trying mine some big data post hoc. Thinking really hard to focus your question, and then designing your experiment around that, will make the downstream analysis trivial. The analysis is hard and costly and time-consuming and maybe even impossible if you don’t think carefully about what you put on the sequencer before you do your sequencing.
What’s one tool, tip, or mindset shift that has made a big impact in your work?
There have been a number of people who have mentored me in my career, but most recently Jeff Gentry, at this company, who really emphasized, and helped me hone, my instinct for ‘right-sizing’ a solution. Avoiding premature optimization, but also avoiding something so slap-dash that you regret it in two months. I think instinct for right-sizing is something that comes with experience, and not to be too ‘sales-y’ but one of the nice things at Fulcrum is that everyone has seen so many projects that even our junior people have a pretty good instinct for the amount of rigor for a given effort, what is the right amount of structure and process. We don’t want to waste time and money today, but we also don’t want to waste time and money in the long term.
What’s a recent project or insight you’re particularly proud of?
I am working on a PacBio long read project right now and I’m just really excited! Every time I get to work on a new library prep technology, or a new sequencing read type, on a new application with long reads I’m thrilled. I’m just stoked about long reads, if you’ve got long reads bring them to Fulcrum! I want to analyze them.
If you could give biotech startups one piece of advice, what would it be?
I have been in three. There’s fifty-thousand things I could say. If I had to choose one it would be to hire very carefully your initial people. And then this goes back to what we were saying about right-sizing your solution, but think very carefully if you need a whole team for this, or do you need people to put a solution in place that a smaller team can then maintain? When do you need to bring certain kinds of expertise in, and do they need to be full-time employees? And then in terms of your full-time employees, are you promising them growth as employees as a best-case scenario trajectory or are you going to need them to be an individual contributor for a long time and are they going to be happy doing that? If that’s the case, hire them to be a good individual contributors and not for management opportunities ‘down the road’.
What’s something outside of work that inspires how you think about problem-solving?
My hobby is rock climbing. Lots of people like rock climbing because it’s both exercise and a little puzzle you get to solve. I’m not a particularly accomplished climber but I do enjoy it. I think it’s a pretty good metaphor for a lot of technical things. You stand on the ground and you look at your route and you think “I know what this is going to be like! I have a plan, it will be fine, I’ll just do the plan.” Then you get up there two-thirds of the way and think “oh, now that I’m closer I can see why this plan is not going to work.” You have to pivot, and be flexible. Those are skills that are very important when you’re doing technical work, particularly doing a new thing that people haven’t done before. You definitely should go in with a plan! But you should be open-minded about what you’re going to do if something unexpected comes up or there were unknown variables adding complexity.