1. Computational thinking in biology
Hong Qin

2. Biological information
DNA
RNA
protein
phenotype
Central dogma
Genome
Transcriptome
Proteome

3. The genetic code
Start and stop codons

4. What is life?
Life feeds on “negative entropy” at the expense of free energy from environment.
Life is governed by the set of universal rules as are other matters in the rest of the universe.
Life is digital by nature (Schrodinger did not know this).
Life is self-replicative.
Things with life “live”, not just “exist”.
… …

5. Biology is digital in nature.
DNA
RNA
protein
phenotype
Genome
Transcriptome
Proteome

6. Computational thinking
A way of thinking that takes advantage of computing.
A way of reasoning.

7. Some key concepts in computational thinking
Iteration, recursion
Multilevel abstraction and conceptualization
Recursion, backtracking,
Modularization, divide-and-conquer approach
Search space and complexity
Random expectation and significance
Permutation and significance
Assessment (cross-validation) and error corrections
Parsimonious reasoning
Multiple test and correction of p-values
Simulation
Prevention of worst-case scenario

8. Cell cycles in biology and iterations in the digital world

9. Self-replication in biology and recursion in the digital world.
Self-replicating viruses
Recursion calls

10. What is recursion?

11. A recursive R function recursive.factorial = function(x) {
if ( x <=1 ) { return( 1 )
} else {
return( x * recursive.factorial( x -1 ) ) ; }
recursive.factorial(4);

12. PCR reaction is recursive in biology and iterative in procedure.

13. Recombination and selection in biology and combinatorial optimization in computing.

14. Example: Permutation and p-value

15. Student’s t-test (equal sample sizes, equal variance)

16. Some tips on writing codes
Think it through, sketch your ideas on a pad
Translate your ideas into codes
Test and debug