Sept 20-26 - Revision history

Damian at 16:46, 18 December 2009

2009-12-18T16:46:15Z

← Older revision		Revision as of 16:46, 18 December 2009
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	*[[Exercise 7.4]]		*[[Exercise 7.4]]
	*[[Exercise 7.5]]		*[[Exercise 7.5]]


			Damian:
			*[[Exercise 7.1D]]
			*[[Exercise 7.3D]]
			*[[Exercise 7.4D]]
			*[[Exercise 7.5D]]

Erika: Week 4 moved to Sept 20-26: more clarity

2009-11-11T03:50:38Z

Week 4 moved to Sept 20-26: more clarity

← Older revision	Revision as of 03:50, 11 November 2009
(No difference)

Erika at 01:02, 1 October 2009

2009-10-01T01:02:08Z

← Older revision		Revision as of 01:02, 1 October 2009
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	<b>Summary for Week 4</b>		<b>Summary for Week 4</b>

	With Chapter 7, "Mutations and Randomization," we ~~learn about~~ 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.		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:

Erika at 01:01, 1 October 2009

2009-10-01T01:01:24Z

← Older revision		Revision as of 01:01, 1 October 2009
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	<b>Summary for Week 4</b>		<b>Summary for Week 4</b>

	With Chapter 7, "Mutations and Randomization," we learn about 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.		With Chapter 7, "Mutations and Randomization," we learn about 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.

	~~...to be continued~~		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

Erika: New page: Return to Bioinformatics Summary for Week 4 With Chapter 7, "Mutations and Randomization," we learn about the random number generator algorithm and how it can be applied to bi...

2009-09-29T15:06:02Z

New page: Return to Bioinformatics Summary for Week 4 With Chapter 7, "Mutations and Randomization," we learn about the random number generator algorithm and how it can be applied to bi...

New page

Return to [[Bioinformatics]]

Summary for Week 4

With Chapter 7, "Mutations and Randomization," we learn about 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.

...to be continued

----
HOMEWORK

Erika:
*[[Exercise 7.1]]
*[[Exercise 7.3]]
*[[Exercise 7.4]]
*[[Exercise 7.5]]