This is a HTML5/Javascript implementation of a scanner that makes a comparison between two methods, namely between Shanon entropy (Information entropy) and self-sequence alignment (Information content). Information entropy (IE) and Information content (IC) are two methods that quantitatively measure information. Here, these parallel results are shown in the form of signals above a given sequence (z). To obtain these signals, the contents of sliding windows (arbitrary length - user defined) are analyzed with the two methods and the values are stored as discrete signals inside a vector. Specifically, here both measure the information in the sequence of characters stored in a variable called z:
var z = "AAAAAACAGGTGAGTAAAAAGCCCGGATTTTTTTTTTTCGCGCGGCGCGGCGGCATTTATTTTCTATTTATCTTCTCTTCTCTTTCTCTTAAAA";Note that on the interface the z sequence can be modified by the user in real-time. This comparison is made to highlight the qualitative differences between information entropy and the new method of information content described as a primary source in the book entitled Algorithms in Bioinformatics: Theory and Implementation. Below, the black line represents the Shannon Entropy and the red line represents the information content over the z sequence. For those interested in the application's chart, it can be downloaded from here.
Live demo: https://gagniuc.github.io/Information-Content-vs-Information-Entropy/
-
Paul A. Gagniuc. Algorithms in Bioinformatics: Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961.
-
Gagniuc and Ionescu-Tirgoviste: Gene promoters show chromosome-specificity and reveal chromosome territories in humans. BMC Genomics 2013 14:278.
-
Gagniuc and Ionescu-Tirgoviste: Eukaryotic genomes may exhibit up to 10 generic classes of gene promoters. BMC Genomics 2012 13:512.
-
Ionescu-Tîrgovişte C, Gagniuc PA, Guja C (2015) Structural Properties of Gene Promoters Highlight More than Two Phenotypes of Diabetes. PLoS ONE 10(9): e0137950.