1. Introduction to Computational Thinking Vicky Chen

2. Fundamental Theorem of Informatics Friedman C P J Am Med Inform Assoc 2009;16:169-170

3. What Informatics Is Not Friedman C P J Am Med Inform Assoc 2009;16:169-170

4. Computational Thinking Computational thinking is a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science. To flourish in today's world, computational thinking has to be a fundamental part of the way people think and understand the world. http://www.cs.cmu.edu/~CompThink/

5. Computational Thinking Analyzing and logically organizing data Data modeling, data abstractions, and simulations Formulating problems so computers may assist Identifying, testing, and implementing possible solutions Automating solutions via algorithmic thinking Generalizing and applying this process to other problems

6. Algorithm A finite list of instructions that describe all required steps to perform a computation, written in general language

7. Programming Steps Specification – What the code should do Design – Pseudocode Implement – Programming Test – Debugging

8. Data Type / Data Structure Integer Floating point Boolean Character String List Dictionary Hash Table

9. Data Types

10. List

11. Dictionary / Hash Table

12. Exercise 1 We have a matrix with mutation information for different tumor samples. How can this data be represented?

13. List of Lists Data is a sparse matrix Stores a lot of extra uninformative information

14. Dictionary

15. Opening Files Mutation matrix contains data on 2337 genes and 779 samples Inputting data by hand is not feasible Data usually read in and processed from files

16. Opening Files

17. Input and print

18. For Loops

19. While Loops

20. Conditional Statements

21. If, else if, else and or not

22. Exercise 2 We have a dictionary that contains tumor sample mutation information. We want to print out a list of tumor samples after receiving a mutated gene of interest from the user.

23. Opening Files Revisited

25. Data Extraction from Files Many files will contain extra information Focus on extracting only pertinent data Applicable to many types of data – Natural language documents (e.g. articles) – Sequence data (e.g. FASTA files) – Files from databases (e.g. NCBI Gene, TCGA) – Etc.

26. Regular Expressions

27. Reusing Code Some code can be useful in multiple situations It is possible to just rewrite (or copy) the code each time – Less efficient – Multiple locations to fix when debugging

28. Functions

29. Exercise 3 We have a document containing human gene information downloaded from NCBI. We want to extract and store the Ensembl ID of each gene with its corresponding gene symbol.