1. Determining Molecular Weight of Unknown Proteins: NASA - PAIR Final Project August 24, 2001 Gregory Frye Jennifer Wright Jennifer Rosales

2. Overall Process: n 8/17/01: Define Standards and comparison of data n 8/20/01: Analyzing data with Spotfinder and Choose best method for analysis n 8/21/01: Work on models that work best for the data n 8/22/01: Receive unknowns for project. Begin analyzing data and applying our model. n 8/23/01: Compile all the information and work on Power Point presentation

3. Unknowns: -Vitelline envelopes and sperm enzymes of Lepidobatrachus Laevis. -Gels 2, 4 and 6

6. Defining the standards n Adobe Photoshop method –able to scrutinize images more n Hardy spotfinder method –grouping bands close together as one band –quicker in finding location of the bands

7. Photoshop vs Hardy method

8. Log Linear: Log MW = a+b(RM)

9. SLIC Model: Log (lnMW)= a+b*ln(-ln(RM))

10. Organization of Project 1.) Find Relative mobility of Standards -We used both Adobe Photoshop and Spotfinder. We decided to use the values of the Adobe Photoshop. 2.) Predict Molecular weight with different statistic models. Models which I tested: RM = Relative Mobility a.) Log MW vs RM^2 (Quadratic model) b.) Log MW vs –LN of RM^2

11. Log MW vs RM^2 PROS & CONS WITH MODEL: 1.) R-Squared is good for the most part. Ranging from :.96 -.99 2.) Predictions are good 3.) But there is a very clear pattern amongst all the residuals. Therefore, we might be able to find a better fitting model.

12. Log MW vs RM^2

13. Log MW v (-LNRM)^2 PROS & CONS OF MODEL: 1.) R-Square values are better than previous model. Most all values are.99 with the exception of three of the standards 2.) Predictions are also better than previous model. All are very close to original MW. 3.) Much more variation in residuals than previous model.

14. Log MW vs (-LNRM)^2

15. Log - Log Model: log(MW) = a + b * log(RM) + c * log(RM)^2

16. Cubic Model: log(MW) = a + b * RM + c * RM^2 + d * RM^3

17. Comparison of 3 statistical models

18. Mean R-Square for models tested:

19. Cubic Model used: Log MW= a+b (RM)+c(RM)^2+d(RM)^3

20. Final Predicted Weights:

23. In Conclusion: n The higher concentration gels spread the sample more, yielding a higher number of proteins. n Finding the relative mobilities of the proteins was done more clearly with the Adobe Photoshop method. n The cubic model was the best of the models that we tried in determining the unknown molecular weight Many thanks go to: Dr. Clevenson Dr. Carroll Dr. Shubin John Handy Virginia Latham