design of experiment, application in biology 2012 petr císař
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Design of experiment, application in biology2012
Petr Císař
Faculty of fisheries and protection of waters
Points of presentation
• Motivation
• Design of experiment
• Introduction
• Main steps
• Advantages
• Application in biology
• Process
• Method
• Results
Faculty of fisheries and protection of waters
Motivation
• Experiment is one of the basic method of human understanding
• Experiment is a scientific method used for testing of hypothesis or existing theories
• It is a bridge between theory and reality
• Why the students do not use sophisticated methods of experiment realization and analysis?• How to design the experiment?• How to analyze the experiment?
Faculty of fisheries and protection of waters
Classical approach
• One factor at a time (OFAT)• Usually we change only factor – rest is fixed• First we change X1 to get optimum and then we fix it and change X2
Real optimum
Response surfaceOptimum found by OFAT method
• OFAT advantages:• Simple
• OFAT disadvantages:• Optimum need not to be found• We do not know the relationship between factors and system response• Impossible to understand to the mutual influence between factors• Number of experiments?• The OFAT experiment has to be repeated for each type of system response
• We do not know the system
Faculty of fisheries and protection of waters
Motivation
• Is it possible to do it better?
• Measure everything under all conditions.
• NO
• Create optimal design of experiment and use statistics to understand to it
• Design of experiment (DOE).
Faculty of fisheries and protection of waters
Design of experiment
DOE – Design Of Experiment • Set of tools for:
• Creation of experimental design • Experiment realization• Experiment analysis
• with optimal number of experiments • Part of Six Sigma methodologies
• Industry standard for process improvement• Used in industry since 1986
• Planed experiment: active change of the process – controlled change of system factors
• Outputs:• Minimal number of measurements• List of important factors• The level of influence of controlled and uncontrolled factors to the system response• Interactions between factors• Mathematical model of the system
Faculty of fisheries and protection of waters
DOE - Main steps
• Identify variables of the system• Identify factors• Select design• Define the levels of factors• Randomize the order of measurements• Realize measurements and record the results
• Analyze data• Evaluate the results• Verify results
Experiment design
Experiment analysis
Faculty of fisheries and protection of waters
DOE - features
• Repetition – determine variance caused by noise
• Randomization – Avoid systematic influence of variables
• Block ordering – the same conditions inside the blocks (operator)
• Balanced design - explore the state space
• Central sample – determine response curvature
factor
Re
spo
nce
The influence of the factor
Faculty of fisheries and protection of waters
DOE
• Problem definition:• Aim determination• Factors and their levels
• DOE response:• Determination of the most important
factors• Determination of main factors
influence and interactions, low number of factors
• Optimization of factors
• Optimization of high number of factors
Experts discussion
Impossible by DOE
First screening
Advanced screening
Optimization
DOE
Faculty of fisheries and protection of waters
DOE – Statistical method
• The math behind DOE is relatively simple
• The students can learn the math by examples
• Tools:• ANOVA – Analysis Of Variance – explore the sources of variance in
the system – influence of the factors• Regression model – determine mathematical description of the
system• Optimization methods - optimization using the mathematical model
of system
• Everything can be show as pretty pictures• We have to understand what is behind !!!
Faculty of fisheries and protection of waters
DOE – Pretty pictures
• Experimental design table Experimental space Set of tools for:
Faculty of fisheries and protection of waters
DOE – Pretty pictures
• Main factors plot Interaction plot
Faculty of fisheries and protection of waters
DOE – ANOVA table
Faculty of fisheries and protection of waters
Application in biology
• Biological experiments:• Typical task: optimization of cultivation conditions
• High level of noise
• Impossible to know all influencing factors
• High number of factors
• Difficult to set experimental conditions to defined values
• Outliers – unpredictable results
• Time consuming experiments
• Repeatability of experiment by other experts
Faculty of fisheries and protection of waters
Maximization of protein amount
• Aim• to optimize production of fusion protein to obtain the highest
amount of protein• optimized protein:
• fusion protein (FP) - maltose binding protein (MBP) and parathyroid hormone (1-34) (PTH)
• Procedure
1. choose variable parameters and methods for measurement
2. create procedure for analysis of amount of fusion protein
3. use DOE for planning and analysis of experiments
4. locate optimum cultivation conditions
5. verify optimum by additionally experiments
Authors: Martina Tesařová, Petr Císař, Zuzana Antošová, Oksana Degtjarik, Jost Ludwig and Dalibor Štys
Faculty of fisheries and protection of waters
• Process• Growth of bacteria under cultivation conditions• Extraction of the amount of the protein – expensive
• Factors and methods – based on expert knowledge• Four factors :
• temperature 25; 37; 42 °C• starting OD 0.1; 0.2• RPM of shaker 150; 200• time of harvest 1; 3; 6; 12; 24; 48 h
Maximization of protein amount
Faculty of fisheries and protection of waters
• Extraction of the amount of protein• Expensive and time consuming• Estimation of the amount of protein
• Based on staining - electrophoresis gel• Calibration based on extraction of protein and size of blob• Blobs marked by manual annotation -> estimation of the amount
of protein• Problem of comparison of blobs between gels – usage of
marker
Maximization of protein amount
Faculty of fisheries and protection of waters
DOE
1. Fractional factorial design – 3 repetitions• Key factors – temperature, time of harvest
Maximization of protein amount
Faculty of fisheries and protection of waters
Maximization of protein amount
DOE
1. Response surface• Localized optimum - temperature: 36.6 °C, start OD: 0.1, RPM of
shaker:150, time of harvest: 7.5 h
Faculty of fisheries and protection of waters
Conclusion
DOE• Optimization of amount of protein• Results
• 93% of the data are covered by the model – biological system• Two key factors found: temperature and time of harvest• Level of significance – 5%• Localized optimum - temperature: 36.6 °C, start OD: 0.1, RPM of
shaker:150, time of harvest: 7.5 h• Optimum verified by 18 testing experiments
• DOE was successfully used for the optimization of biological experiment
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