HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets
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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/94636/1/WanHaslinaHassan2021_HDGSelectANovelGUIBasedApplication.pdf http://eprints.utm.my/id/eprint/94636/ http://dx.doi.org/10.1371/journal.pone.0246039 |
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| Summary: | 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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