Classification of RNA Sequences using Complex Network and Information Theory
Performs the classification methodology using complex network and entr...
Creates an untargeted graph from a biological sequence
Creates a feature matrix using complex network topological measures
Creates an entropy curve
Calculates the entropy
Filters the edges
Compares the matrices
Calculates the maximum entropy
Rescales the results between values from 0 to 1
Selects the edges of the adjacency matrix
Trains the algorithm to select the edges that maximize the entropy
It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of maximum entropy for the purpose of making a classification between the classes of the sequences. There are two data present in the 'BASiNET' package, "mRNA", and "ncRNA" with 10 sequences. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples.