Algorithm for classification of biological data based on data mining

Autor: Eduardo Moniz Garcia, Simone A. Siqueira da Fonseca, Jorge R. Beingolea
Rok vydání: 2019
Předmět:
Zdroj: 2019 IEEE 1st Sustainable Cities Latin America Conference (SCLA).
DOI: 10.1109/scla.2019.8905627
Popis: The study of genetic changes is regarded as being of paramount importance, since it can yield a greater understanding of the genetic expression and its consequences, such as: the anticipated forecast of certain types of diseases. The task of identifying changes in the DNA sequence (deoxyribonucleic acid), hitherto not described after next generation sequencing analysis has become one of the main activities of bioinformatics due to the capacity to analyze and interpret a wide range of genetic data. Numerous software applications were designed for purposes of sequence aligning, and subsequently identifying genetic changes. This study aims to establish a method that prepares genomic data and the discovery of existing correlations between changes in DNA sequence and other nitrogen bases, with the use of association rule algorithm using data mining, aiming to identify correlations between nucleotides of a DNA sequence, the correlation is made between nucleotides that significantly alter the DNA sequence and the other nucleotides of the analyzed DNA sequence. The purpose of this study is to identify nucleotide correlations of DNA sequences still unknown and to acquire a better understanding of the DNA structure.
Databáze: OpenAIRE