PROTEOMICS: GROUP 7 Aaron Simo, Antolino Venegas, & Daniel Weisman

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Text of PROTEOMICS: GROUP 7 Aaron Simo, Antolino Venegas, & Daniel Weisman

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  • PROTEOMICS: GROUP 7 Aaron Simo, Antolino Venegas, & Daniel Weisman
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  • Project 1 To compare the standards of constant concentration gels: Determine the best predictive models for each gel concentration and then do a comparative analysis. Extrapolate the lightest molecular weight able to be captured for each concentration.
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  • Source Data 7.5% acrylamide concentration gels Three standards on two gels 10% acrylamide concentration gels Two standards on two gels 12% acrylamide concentration gels Five standards on four gels 15% acrylamide concentration gels One standard on one gel
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  • Gel Sample
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  • Methods Cut & paste the scanned gels from the protein start point. Measure each protein bands centimeters traveled and find the relative mobility by dividing the centimeters traveled by the dyefront. Plot relative mobility against the Log of the molecular weight and add trend lines. Find the R 2 adjusted for the trend lines as an indicator of the best fitting models.
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  • Methods (Continued) Using Minitab, construct the confidence intervals for the best fitting trend lines. Using Minitab, extrapolate the lightest molecular weight that can be captured by each gel according to each gels model with the tightest confidence interval.
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  • Decisions Skewed gel columns were rotated, sometimes individually, to align with the Photoshop rulers. Band measurements were weighted to higher saturation. A higher saturation is indicative of a higher protein count, and we wanted the measurements to be representative of the median of the proteins population.
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  • Decisions (Continued) Only the first standard column per gel was used so that there would be equal amounts of data per gel concentration for accurate comparisons. Unequal number of data would lead to great differences in degrees of freedom and make the concentrations not comparable. The best models were determined by the smallest confidence intervals. A models predictive value is determined by the confidence interval, so the model with the tightest confidence interval would represent the model with the greatest predictive value.
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  • Decisions (Continued) Extrapolation for the lightest molecular weight was done using the models with the tightest confidence intervals.
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  • Discovery We discovered an abnormally large difference between the relative mobility of the 12% Sea Urchin Gels and the 12% Frog Gels. Because specific gel concentrations have generally correlative relative mobility, we plotted each set of relative mobility standards against the molecular weight and found that the 12% Frog Gel Set is most likely mislabeled and truly a gel concentration around 15%.
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  • Conclusions The 12% concentration frog sample is most likely not truly 12%, but a higher concentration somewhere in the vicinity of 15%. For differentiation of the heaviest proteins, a 10% acrylamide concentration provides the tightest confidence intervals, but for lighter proteins a 12% or higher is best.
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  • Conclusions (Continued) Gel concentration lower limits for molecular weight: 7.5% limits at 45,500 daltons 10% limits at 44,400 daltons 12% Sea Urchin limits at 25,100 daltons 12% Frog limits at 19,900 daltons 15% limits at 14,200 daltons
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  • Conclusions (Continued) The high correlation suggests the possibility of using the exact same model for all gels of the same concentration and specific models for specific Log of the molecular weights.
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