"There's no such thing as bad data..."
When I got to my first 20.109 class, I felt very confident. I've been working in a Course 20 UROP culturing cartilage explants for the past two years, so I thought Mod 1 would be a breeze. I already knew to spray everything with ethanol, stay away from the aspirator, and change pipette tips between stocks.
However, my first big challenge of 109 was figuring out different volumes of stocks to use for goal concentrations. While I have made dilutions many times in my lab, it's typically for the same media each time. Additionally, I do the calculations in the quiet of my lab cubicle, rather than in the middle of loud classroom under the supervision of a stellar lab partner and peer! So- I was stressed. I started scribbling on the back of my lecture notes and pressing clear on my iPhone calculator. My lab partner, Emily, had finished the calculations before I even opened the calculator app! That is when I learned the utility of using Excel to do C1*V1=C2*V2. Never again will I struggle to do dilutions!
The next few weeks went okay. I found the 109 assignments to be helpful benchmarks in the overall preparation for our data summary. However, when we started to look at our DSF and PPIase data, my heart sank. The melting temperatures were all basically the same. And our PPIase data was a wreck. In one condition, the confidence interval was four times the size of the actual data bar. In the rest, our activity was all increasing with bound ligands, which was the opposite of what we were expecting.
In my UROP I had never found data that was this unexpected. And even worse, I still found it overwhelming to analyze the data on Excel! Something as simple as "plug in the formula" turned into a sea of excel sheets, other peers' excel sheets, duplicate copies of excel sheets, and "This Excel Notebook unexpectedly quit."
But eventually my lab partner shared some of her excel expertise with me. And while our data wasn't what we expected, we were able to use our results to think more critically about our experiment. Thinking about all of the things that could have "gone wrong" helped us to really understand what the experiments were about and to visualize how FKBP12 and our ligands may have been interacting.
-Christina Rossitto, 3/18/18
However, my first big challenge of 109 was figuring out different volumes of stocks to use for goal concentrations. While I have made dilutions many times in my lab, it's typically for the same media each time. Additionally, I do the calculations in the quiet of my lab cubicle, rather than in the middle of loud classroom under the supervision of a stellar lab partner and peer! So- I was stressed. I started scribbling on the back of my lecture notes and pressing clear on my iPhone calculator. My lab partner, Emily, had finished the calculations before I even opened the calculator app! That is when I learned the utility of using Excel to do C1*V1=C2*V2. Never again will I struggle to do dilutions!
The next few weeks went okay. I found the 109 assignments to be helpful benchmarks in the overall preparation for our data summary. However, when we started to look at our DSF and PPIase data, my heart sank. The melting temperatures were all basically the same. And our PPIase data was a wreck. In one condition, the confidence interval was four times the size of the actual data bar. In the rest, our activity was all increasing with bound ligands, which was the opposite of what we were expecting.
In my UROP I had never found data that was this unexpected. And even worse, I still found it overwhelming to analyze the data on Excel! Something as simple as "plug in the formula" turned into a sea of excel sheets, other peers' excel sheets, duplicate copies of excel sheets, and "This Excel Notebook unexpectedly quit."
But eventually my lab partner shared some of her excel expertise with me. And while our data wasn't what we expected, we were able to use our results to think more critically about our experiment. Thinking about all of the things that could have "gone wrong" helped us to really understand what the experiments were about and to visualize how FKBP12 and our ligands may have been interacting.
-Christina Rossitto, 3/18/18
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