Dimension reduction methods for microarray data: a review Page 1 AIMS Bioengineering, 4(2):
179-197. DOI: 10.3934/bioeng.2017.2.179 Received: 27 November 2016 Accepted: 01 …

Cancer disease has been classified as a perilous disease for humans, being the second
leading cause of death globally. Even advanced-stage diagnosis may not be effective in …

Purpose PTEN mutation status is a pivotal biomarker for glioblastoma. This study aimed to
establish a radiomic signature to predict PTEN mutation status in patients with glioblastoma …

This paper develops a new algorithm which selects the appropriate feature set and
overcomes the challenges with microarray data. Initially, it balances the dataset and then …

The term “big data” characterizes the massive amounts of data generation by the advanced
technologies in different domains using 4Vs–volume, velocity, variety, and veracity-to …

Random Forests are powerful classification and regression tools that are commonly applied
in machine learning and image processing. In the majority of random classification forests …

Botnets are one of the major threats today and one of the main reasons for this is its
capability to hide in the network. It is not easy to detect Botmaster, the one who controlled …

High Dimensional cancer microarray is devilishly challenging while finding the best features
for classification. In this paper a new algorithm is proposed based on iterative qualitative …

Microarray technology is widely used to report gene expression data. The inclusion of many
features and few samples is one of the characteristic features of this platform. In order to …

Purpose: The purpose of this research is to apply dimensionality reduction methods to fetch
out the smallest set of genes that contributes to the efficient performance of classification …