Difference between revisions of "Sept 20-26"
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<b>Summary for Week 4</b> | <b>Summary for Week 4</b> | ||
| − | With Chapter 7, "Mutations and Randomization," we | + | With Chapter 7, "Mutations and Randomization," we are introduced to the random number generator algorithm and how it can be applied to bioinformatics. Specifically, the random number generator allows users to select random locations in a string or array and simulate mutations in DNA sequences. The random number generator is, in fact, an algorithm and therefore is inherently not fully random. In order to ensure truly random outputs, the author cautions that a generator must be seeded in as random manner as possible. |
Main skills taught in this chapter are: | Main skills taught in this chapter are: | ||
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*[[Exercise 7.4]] | *[[Exercise 7.4]] | ||
*[[Exercise 7.5]] | *[[Exercise 7.5]] | ||
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| + | Damian: | ||
| + | *[[Exercise 7.1D]] | ||
| + | *[[Exercise 7.3D]] | ||
| + | *[[Exercise 7.4D]] | ||
| + | *[[Exercise 7.5D]] | ||
Latest revision as of 11:46, 18 December 2009
Return to Bioinformatics
Summary for Week 4
With Chapter 7, "Mutations and Randomization," we are introduced to the random number generator algorithm and how it can be applied to bioinformatics. Specifically, the random number generator allows users to select random locations in a string or array and simulate mutations in DNA sequences. The random number generator is, in fact, an algorithm and therefore is inherently not fully random. In order to ensure truly random outputs, the author cautions that a generator must be seeded in as random manner as possible.
Main skills taught in this chapter are:
- Seeding the random number generator
- Control Flow
- Randomly selecting an element of an array
- Simulating DNA mutations
- Generating random DNA
- Analyzing DNA
HOMEWORK
Erika:
Damian:
