Individually, (1/100 points) Compose an entertaining, exhilarating, thought-provoking, or melancholy Haiku on the subject of DNA melting.

As a team, (3/100 points) Document your data collection procedure. Report instrument settings for each trial, including control software parameters. Refer to the lab manual wiki pages when appropriate, and describe any changes you made.

As a team, (10/100 points) Plot all of your raw data (as fluorescence vs. block temperature) on the smallest number of axes that clearly conveys the dataset. Include only data generated by your own group.

• Data from the many sample runs overlaps, which makes presenting so much data on a small number of axes a real challenge.
• Devise a combination of line colors, line thicknesses, and marker symbols that produces clear plot. If two sample types have a great deal of overlap, there may be no choice but to plot them on separate axes.
• One approach that works well for some datasets is to plot a subsampled version of each trial using discrete markers. Vary the color and form to differentiate between sample types and individual trials.

Individually,

• Document the regression model you used to analyze your data
  • See Assignment 9, Part 1: model function
  • Explain the model parameters using bullet points or in a table.
• Plot $ V_{f,measured} $ and $ V_{f,model} $ versus $ T_{block} $ for a typical run of each samples type. Use the smallest number of axes that clearly conveys the data.
• Provide a table of the best-fit model parameters and uncertainties for each experimental run. Also include the estimated melting temperature for each run.
• For a typical curve, plot residuals versus time, temperature, and fluorescence, (example plot).
• For at least one experimental trial, plot $ \text{DnaFraction}_{inverse-model} $ versus $ T_{sample} $ (example plot). On the same set of axes plot DnaFraction versus $ T_{sample} $ using the best-fit values of ΔH and ΔS. Finally, plot simulated dsDNA fraction vs. temperature using data from DINAmelt or another melting curve simulator.

As a team,

1. Results:
   • Identify your unknown sample (or state that your investigation did not provide a conclusive answer).
   • Quantify the confidence you have in your result.
   • How do your estimates for $ \Delta H, \Delta S $ and T_m compare to the predicted values from DINAmelt (or your favorite software)?
   • How do your estimates for $ \Delta H, \Delta S $ and T_m compare to results from other groups and/or instructor data?
2. Discussion:
   • LC green fluorescent dye saturates the binding sites of the double-stranded DNA. SYBR green, in turn, is non-saturating. Compare the melting temperatures that you measured for Sample A (20 bp, complete match, 100mM salt) to a measurement you made previously using the 'beater DNA'. The beater DNA is the same sequence and salt concentration as sample A, but prepared with SYBR green. Which dye would you use if you wanted to make the most accurate measurement of T_m? Why?
   • Discuss the validity of assumptions in the regression model.
   • Discuss any atypical results or data you rejected.
   • Discuss significant error sources.
     • Consider the entire system: the oligos, dye, the experimental method, and analysis methodology, and any other relevant factors.
     • Indicate whether each source likely caused a systematic or random distortion in the data.
     • Present error sources, error type and their resultant uncertainty on your data and results in a table, if you like.
   • Discuss additional unimplemented changes that might improve your instrument or analysis.