A graph-based gene selection method for medical diagnosis problems using a many-objective PSO algorithm.
Journal:
BMC medical informatics and decision making
Published Date:
Nov 27, 2021
Abstract
BACKGROUND: Gene expression data play an important role in bioinformatics applications. Although there may be a large number of features in such data, they mainly tend to contain only a few samples. This can negatively impact the performance of data mining and machine learning algorithms. One of the most effective approaches to alleviate this problem is to use gene selection methods. The aim of gene selection is to reduce the dimensions (features) of gene expression data leading to eliminating irrelevant and redundant genes.