FND-STA-Information theory

Concepts of Information Theory

(Information theory)

 

Abstract:

A brief introduction to entropy and information: information theory appled to amino acid disributions.

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Objectives: This unit will ... ... introduce concepts of the foundations of information theory and its application to amino acid distributions.

Outcomes: After working through this unit you ... ... can calculate the informational entropy in a distribution of observed amino acids; ... are familar with various ways to define the informational entropy of reference distributions; ... can calculate information as the difference between expected and observed entropy.

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Deliverables:

• Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
• Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.
• Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.

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Prerequisites:
You need the following preparation before beginning this unit. If you are not familiar with this material from courses you took previously, you need to prepare yourself from other information sources:

• Calculus: functions and equations; polynomial functions, logarithms, trigonometric functions; integrals and derivatives; theorem and proof.
• Geometry: length, area, volume; Euclidian and non-Euclidian space.
• Probability: event, probability, hypothesis and significance.
• Physical chemistry: Kinetics and equilibria, transition states, chemical reactions; enthalpy, entropy and free energy; acid-base equilibria, Boltzmann's law.

This unit builds on material covered in the following prerequisite units:

• BIN-Sequence (Sequence)

 

 

 

Contents

Task:

• Read the introductory notes on concepts of Shannon's theory of information as applied in bioinformatics.

Self-evaluation

Notes

Further reading, links and resources

 

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If in doubt, ask! If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.

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About ...
 
Author:

Boris Steipe <boris.steipe@utoronto.ca>

Created:

2017-08-05

Modified:

2017-10-23

Version:

1.0

Version history:

• 1.0 First live version
• 0.1 First stub

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