Entropy is a measure of the uncertainty in a random variable. This application calculates the entropy of text. The current example calculates the entropy of sequence "TTTAAGCC". In the context of information theory the term "Entropy" refers to the Shannon entropy:
Which can also be written as:
Where n represents the total number of symbols in the alphabet of a sequence and pi represents the probability of occurrence of a symbol i found in the alphabet. For more detailed information on entropy please see the specialized chapter from the book entitled Algorithms in Bioinformatics: Theory and Implementation.
Live demo: https://gagniuc.github.io/Entropy-of-Text/
- Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.