1. Modeling and Computational Tools for Contemporary Biology By Jeff Krause, Ph.D. Shodor 2010 NCSI/iPlant CBBE Workshop

2. What is Computational Biology? 1.The scientific method enhanced: – Observe -> Explain -> Predict -> Test – But, with the explanation in the form of a computational model 2.Using computers to find meaning in data – Performing calculations – Filtering out less interesting cases – Presenting data in ways that are easy to interpret

3. Computers are Really Dumb … But they do what they’re told, They do it quickly They don’t get distracted And they don’t make many mistakes People are Really Smart … They can solve hard problems But they often get distracted and make mistakes

4. Why do we need computational modeling in the classroom? Dynamic models are used to represent and understand how change happens based on cause and effect In teaching: Models can be used to help students go from a list of facts to a functional understanding In science: Models can be used to evaluate whether our understanding of a natural phenomenon is sufficient to account for it’s behavior

5. Computational Science Pedagogy Seeing a dynamic simulation - help students to form a functional representation Adjust a simulation – learn about the system by studing it with virtual experiments Modify a model – practice abstracting to an algortihmic explanation (mechanistic explanation) Create a model – put the pieces together

6. Things move, interact and transform in living (and non-living) systems “Things” tend to redistribute themselves to fill a space. When two “things” come together, one, or both, of them is changed. Each moment, some of the “things” will become something else.

7. Biological macromolecules are the building blocks of life Lipids, DNA and protein don’t occur naturally in high abundance. Cell’s expend energy to produce them in a regulated way in order to maintain their compartmental order, and control over the chemical and physical processes of life. – DNA - information storage – Lipids - membrane structure – Proteins - molecular workhorses

8. Some ground rules for chemical kinetics First order – Rate depends on the amount of a single species – Example - some of the enzyme-substrate complex will form product and release enzyme – Simple exponential kinetics for irreversible reaction Consider each basic step individually – most can be reduced to a first, or second-order process

9. More ground rules for chemical kinetics Steps that involve more than two species should be treated as multiple steps involving two species, where one of the species is a complex of multiple species Second order – Rate depends on the amount of two species – Example - substrate and enzyme combine to form a complex (or, a second substrate combines with the complex to form a two-substrate complex) – Kinetics

10. The NCSI Library Will Go Here

11. Exponential Growth Integrated rate equation P t =P 0 e -kt allows us to calculate P t exactly* at any time (t) *were still likely to use a calculator or computer, so some estimation will be involved

12. Sometimes there is no integrated rate equation What can we do if we don’t have an integrated rate equation to calculate our population exactly? Numerical integration

13. Numerical Integration Euler Method: first-step 1 Calculate the slope at the initial time

14. Euler Method: first-step 2 Use the slope at the initial time to estimate the value of the function after a time-step

15. Euler Method: first-step This estimated value will serve as the initial time for the next interval

16. Euler Method: second-step 1 Calculate the slope at the estimated value

17. Euler Method: second-step 2 Use the slope at the initial time to estimate the value of the function after the next time-step

18. Euler Method: second-step Can Euler do better than this?

19. Euler Method at Higher Resolution: first-step A smaller time-step results in an estimated value with less error than after a larger time-step

20. And we are able to adjust the slope closer to that of the actual function Euler Method at Higher Resolution: second-step

21. Taking more time-steps results in a better estimate of the functions value at a particular time Euler Method at Higher Resolution: comparison

22. Euler Method at Higher Resolution: third-step

23. Euler Method at Higher Resolution: fourth-step

24. Euler Method at Higher Resolution: comparison

25. Higher-Order Numerical Methods: Runge-Kutta 2 Start by finding simple Euler estimate for population at current time

26. Higher-Order Numerical Methods: Runge-Kutta 2 Estimate the slope after the time-step based on the simple Euler estimate

27. Higher-Order Numerical Methods: Runge-Kutta 2 Average the slopes at either end of the interval and use the average slope to estimate the population after the time-step

28. Higher-Order Numerical Methods: Runge-Kutta 2 Repeat the steps: Estimate the initial slope, estimate the final slope, average the slopes to estimate the population

29. Higher-Order Numerical Methods: Runge-Kutta 2

30. Comparison of Simple Euler and Runge-Kutta 2

31. Higher resolution improves Runge-Kutta 2 estimates