A novel gene ranking method using Wilcoxon rank sum test and genetic algorithm

Saha, Sujay; Seal, Dibyendu Bikash; Ghosh, Anupam; Dey, Kashi Nath

doi:10.1504/ijbra.2016.078236

Cited by 11 publications

(7 citation statements)

References 16 publications

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“…This method was used in the literature for the pre-selection of genes [ 60 , 61 ], and it was shown to produce a powerful statistical result, especially when the data are severely skewed and approximately symmetric [ 62 ]. Usually, at the end of the analysis, WRS will give the rank of the genes, beginning with the most discriminative genes and proceeding to the less discriminative ones.…”

Section: Methodsmentioning

confidence: 99%

Selection and classification of gene expression in autism disorder: Use of a combination of statistical filters and a GBPSO-SVM algorithm

2017

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In this work, gene expression in autism spectrum disorder (ASD) is analyzed with the goal of selecting the most attributed genes and performing classification. The objective was achieved by utilizing a combination of various statistical filters and a wrapper-based geometric binary particle swarm optimization-support vector machine (GBPSO-SVM) algorithm. The utilization of different filters was accentuated by incorporating a mean and median ratio criterion to remove very similar genes. The results showed that the most discriminative genes that were identified in the first and last selection steps included the presence of a repetitive gene (CAPS2), which was assigned as the gene most highly related to ASD risk. The merged gene subset that was selected by the GBPSO-SVM algorithm was able to enhance the classification accuracy.

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Section: Methodsmentioning

confidence: 99%

Selection and classification of gene expression in autism disorder: Use of a combination of statistical filters and a GBPSO-SVM algorithm

2017

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“…Hence, some researchers have used the TT filter as the only step of gene selection [ 55 , 56 ]. Also, WRS filter was effectively used for the pre-selection of genes [ 57 , 58 ], especially when the data are associated with high variance [ 59 ].…”

Section: Methodsmentioning

confidence: 99%

HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets

Hameed

Hassan

et al. 2021

PLoS ONE

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The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.

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“…This combination leads to an approach that is faster and more practical from an economic point of view. A group of optimum feature selection techniques was used in this paper, including entropy criteria, 38 Student t test, 39 Wilcoxon signed‐rank test, 40 ROC curve, 41 and Bhattacharya coefficient 42 . To find the analogies of the average of the two groups, Student t test was conducted, and the p and t values of the obtained attributes of the two sets were obtained.…”

Section: Introductionmentioning

confidence: 99%

Implementation of convolutional neural network categorizers in coronary ischemia detection

Wei

Gao

Kumar

et al. 2020

Int J Imaging Syst Tech

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The heart is one of the most important and sophisticated organ of the human body. Coronary ischemia is a condition in which the coronary muscles do not receive sufficient blood and oxygen because of blocked or tightened heart vessels. This syndrome is called cardiac vessel illness. There have been numerous attempts to detect the impact of cardiac vessel illness on the heart muscles using noninvasive experiments. Most of the effects of ischemia as well as severe cardiac conditions on the muscles of the ventricle parts can be detected using ultrasonic images. If treatment is provided to suspected cases in the early stage of cardiac vessel illness, the chance of survival is high; for this, many software‐based detection approaches have been used. In this study, we propose an approach that can automatically diagnose the cardiac artery disease by using the cardiac echo images of the four parts of the heart.

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A novel gene ranking method using Wilcoxon rank sum test and genetic algorithm

Cited by 11 publications

References 16 publications

Selection and classification of gene expression in autism disorder: Use of a combination of statistical filters and a GBPSO-SVM algorithm

Selection and classification of gene expression in autism disorder: Use of a combination of statistical filters and a GBPSO-SVM algorithm

HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets

Implementation of convolutional neural network categorizers in coronary ischemia detection

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