After completing my fourth week of the BSURF program, I have a better understanding of my role and what to expect in the lab. Most of my time in the lab revolves around a computer screen, while a small portion of my time is spent doing hands-on things. But my lab mentor tells me that thorough background research, careful planning of experiments, and careful data analysis take most of a bench scientist’s time, and not the actual bench work running the experiments. This ascertains that the best science possible is being done, to obtain data in a purposeful and hypothesis-driven manner.
With my project, there is a great emphasis in studying inflammatory breast cancer in an in vitro model. My time spent doing hands-on protocols revolve shadowing the graduate student, Risa, producing media for cells, cell culturing, splitting cells, and imaging the progression of tumor emboli via a microscope.
As mentioned earlier, most of my time is spent in front of the computer screen. I am in front of a screen because that is where the data is kept. Using computer software is how I can calculate the size of the tumor emboli growth quantitatively and use that information to produce graphs. However, graphs are tricky, because there are multiple of ways of interpreting the data depending on how you choose to represent and graph the data, and what you are comparing. Furthermore, what makes the process more complicated is finding the right way to convey the information to others, in order to produce a visual result that speaks to the postulates made during hypothesis formation. The foundation of science is built around discovery and sharing those discoveries with the public, and therefore the information scientists choose to share should be able to be understood by others, even sometimes intentionally by the general public. These past few days I have spent a lot of time ensuring that the way I chose to present my data is visually easy to understand and is able to get the point across that I am trying to make. There are some statistical analyses that we have done as well with the graphs to further speak to the significance of the results and trends we have identified from the data.
I am enjoying my time in the lab; I feel that I now understand more of the molecular and biological reasoning behind my project than I did in the beginning. Most of my days may be in front of a screen, but each day there are advancements in my project and I find out more about the data I have or find better ways to present my data to other people. What I have learned so far with this experience is that there is so much data on science projects out there, but it takes time to interpret it correctly. Hopefully, by the end of this program, I will be able to share my data in a way that is meaningful and easily related to my audience.
