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Computational thinking in biology

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Presentation on theme: "Computational thinking in biology"— Presentation transcript:

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


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