The Witchcraft of Wet-Lab
EMMA ZAWILA Conjure up an image for the word “research”: you might imagine a lone figure standing in a white coat, hunching over a complicated arrangement of vials and test tubes. This type of research, referred to as wet lab, is actually only a fraction of all scientific research.
With technology rapidly expanding and finding new applications within science every day, modeling software itself has formed another type of scientific research named computational research.
Computational research lends itself as a means of speeding up the often tedious work involved in wet lab, providing a more clear depiction of what is occurring in some process or reaction. However, even as technology “takes over the world,” wet lab research isn’t likely to be an endangered species of research for a long, long time.
Karan Kathuria, an undergraduate researcher in the Zhang Lab, offers some insight into the importance of wet lab research. Kathuria, a wet lab advocate, remarks, “It’s slow. The labor that’s involved, the amount of time that you put into the lab is not proportional to the amount of results that you get.”
He continues to explain the reason for this: often times in wet lab research, there’s not a clear-cut result that one can rely on. The hypothesis could be wrong; the dependent variables could be off. The level of accuracy needed for running an experiment is extremely high. It’s leviosa, not leviosa.
Kathuria makes a comment on how the uncertainty of the results can create an almost superstitious environment; “human error and chance are a big part of scientific research, so as much as you try to minimize that, there’s still going to be some variation in terms of what will happen when you actually have your experiments, and that’s where the superstition of research comes in which is odd to say. Science is pretty superstitious.”
He later explains that much of this superstition comes from people new to wet lab research who are amazed by the varying results from the same variables. Researches often have to perform the same tests many times over so as to reduce the levels of inaccuracy by using multiple trials. Quantity over quality reigns supreme in wet lab, making it a slow and tedious process at times.
Computational research seems like the obvious solution to this problem. Variables are plugged in and results are chugged out. Results are fast and efficient, saving time for the bright minds involved in research to analyze rather than do the labor-intensive and occasionally mind-numbing work of wet lab.
However, the limitations of computational research are the faults that occur from working with a model rather than a real subject. Kathuria explains, “With a computer, you make a lot of assumptions when you begin a project. Those assumptions might in themselves might be faulty.” Not all of the minuscule variables could have been considered, possibly resulting in an inaccurate representation of the real experiment. There’s almost more illusion within computational research because of an often misguided assumption of better accuracy since the variable are controlled and constant
With wet lab, there’s no false misconception of successful results where there shouldn’t be because the outcome is determined by real physical reactions and processes. In this way, wet lab research, although tedious and occasionally frustrating, is more accurate than computational research.
Kathuria continues clearing up misconceptions about research, one being that wet lab research is done in isolation. While he acknowledges the lack of communication between labs because of competition for publishing, he focuses on the team-based research done within labs and the advantages of teams. “That diversity of thought leads you to have better answers. It’s that variety of experiences that really allows you to solve problems.”
The crux of research, both computational and wet lab, lies in curiosity and investigation: “Questioning in research is one of the most important things. That’s what causes you to think about the problem and think about what is causing this to happen. If you can’t find an answer for it, that’s when you do more research into it.”