Open AccessAn Analysis of Breast Cancer DNA Sequences Using Particle Swam Optimization
Author(s) -
K. Lohitha Lakshmi,
P. Bhargavi,
S. Jyothi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.7.20572
Subject(s) - breast cancer , anticipation (artificial intelligence) , particle swarm optimization , malignancy , dna , cancer , dna sequencing , event (particle physics) , computer science , computational biology , biology , bioinformatics , algorithm , artificial intelligence , genetics , physics , astrophysics
Conceptual Breast tumour conclusion, examination, and visualization are essential research challenges in Bioinformatics. Bosom tumour analysis incorporates recognizing of malignancy bumps and ordinary tissue. Investigation incorporates the present phase of the malignancy tissue and anticipation incorporates expectation of repeat of the bosom tumour in future ages in light of structure and game plan of the individual DNA succession. This paper investigations bosom disease DNA succession to anticipate event of bosom tumour utilizing Particle Swarm Optimization (PSO).PSO procedure is a populace based pursuit calculation that mirrors the social conduct of swam. As the piece of investigation of bosom disease in human, the DNA arrangements of ordinary bosom tissue are contrasted and DNA groupings of bosom tumour tissue utilizing PSO... The distinction between the ordinary and breast cancer disease DNA sequences are broke down in view of the summarized values generated by applying PSO algorithm.