Open AccessHDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets
Author(s) -
Shilan S. Hameed,
Rohayanti Hassan,
Wan Haslina Hassan,
Fahmi F. Muhammadsharif,
Liza Abdul Latiff
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0246039
Subject(s) - computer science , gene selection , graphical user interface , support vector machine , selection (genetic algorithm) , identification (biology) , machine learning , data mining , interface (matter) , user friendly , artificial intelligence , gene , microarray analysis techniques , operating system , biochemistry , chemistry , gene expression , botany , bubble , maximum bubble pressure method , biology
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.