BME103 s2013:TEMPwu3

BME 103 Spring 2013	Home People Lab Write-Up 1 Lab Write-Up 2 Lab Write-Up 3 Course Logistics For Instructors Photos Wiki Editing Help
OUR TEAM Name: Student Role(s) Name: Student Role(s) Name: Student Role(s) Name: Student Role(s) Name: Student Role(s) LAB 3 WRITE-UP Original System: PCR Results PCR Test Results Sample Name ng/mL Conclusion (pos/neg) Positive Control --- N/A Negative Control --- N/A Tube Label:___ Patient ID: ____ rep 1 --- Tube Label:___ Patient ID: ____ rep 2 --- Tube Label:___ Patient ID: ____ rep 3 --- Tube Label:___ Patient ID: ____ rep 1 --- Tube Label:___ Patient ID: ____ rep 2 --- Tube Label:___ Patient ID: ____ rep 3 --- Bayesian Statistics These statistics are based upon all of the DNA detection system results for 34 hypothetical patients who were diagnosed as either having cancer or not having cancer. Bayes Theorem equation: P(A|B) = P(B|A) * P(A) / P(B) Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal. A = [text description] = [frequency shown as a fraction] = [final numerical value] B = [text description] = [frequency shown as a fraction] = [final numerical value] P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value] P(A|B) = [answer] Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal. A = [text description] = [frequency shown as a fraction] = [final numerical value] B = [text description] = [frequency shown as a fraction] = [final numerical value] P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value] P(A|B) = [answer] Calculation 3: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal. A = [text description] = [frequency shown as a fraction] = [final numerical value] B = [text description] = [frequency shown as a fraction] = [final numerical value] P (B|A) = [text description] = [frequency shown as a fraction] = [final numerical value] P(A|B) = [answer] New System: Design Strategy We concluded that a good system Must Have: [Must have #1 - why? short, ~4 or 5 sentences] [Must have #2 - why? short, ~4 or 5 sentences] We concluded that we would Want a good system to have: [Want #1 - why? short, ~4 or 5 sentences] [Want #2 - why? short, ~4 or 5 sentences We concluded that a good system Must Not Have: [Must Not Have #1 - why? short, ~4 or 5 sentences] [Must Not Have #2 - why? short, ~4 or 5 sentences] We concluded that a good system Should Avoid: [Should Avoid #1 - why? short, ~4 or 5 sentences] [Should Avoid #2 - why? short, ~4 or 5 sentences] New System: Machine/ Device Engineering DESIGN STRATEGY We chose to include these new features Feature 1 - explanation of how this addresses any of the the Must Have/ Must Not Have items in the Feature 2 - description * Etc. [OR] We chose keep the devices the same as the original system [Short paragraph explaining why the original system satisfies the design needs that you listed above] DESIGN APPROACH Protocols Materials PCR Protocol DNA Measurement Protocol Research and Development Background on Disease Markers Primer Design Illustration