Deep Breaths and Caffeine

A deep breath of fresh air... Silence.

That was the feeling I got after I clicked the upload button on Stellar to finally submit my Mod 2 research article. The entire Saturday that the research article was due on was a bit of a blur for me. After my daily dose of caffeine, I locked myself in my room and my brain went on overdrive. My heart was racing, my fingers were yakking away at the keys as fast as humanly possible, and I felt as if this was the final countdown.

From this experience, I learned that writing a scientific manuscript is very much different than any other types of writing that I had exposure to. Unlike a literature paper that I would have written for my high school language classes, this research article was not the place to add fluffy, complicated vocabulary and show off your knowledge of complex sentence structure. The more I found myself gravitating to use flowery language to describe simple tissue culture procedures, the more I had to mentally check myself and delete said extra words. I also found it very helpful to do a huge amount of background research on scientific journal databases, such as Nature, and type in key words that were related to your figures' results. This especially applied for analyzing the results in the discussion section and coming up with a storyline to the report. I really enjoyed reading up on different authors' perspectives on the same result, such as p21 over expression in cancer cells, because it helped me really appreciate 20.109. I realized that the research that we have done in Mod 2 is very relevant to today's society, and I think sometimes it is hard to see a bigger goal of the research when each day's procedures are planned out in advance. I also really found it helpful to look at the figures that were used in other articles for some inspiration, as sometimes it can be mind boggling how to create a figure that clearly yet simply represents NHEJ and HR. In order to understand the R-data, I also found it useful to search up specific functions in R again and look up sample data that was collected using the same bioinformatic tool with a previous research article. When editing my methods section, I found it very helpful to re-read things multiple times to determine which words were just unnecessary, and specifically read it out loud. All in all, I think this experience strengthened my ability to understand technical jargon and to see the bigger picture.