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

ABSTRACT: 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.

SUBMITTER: Hameed SS

PROVIDER: S-EPMC7842997 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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

Hameed Shilan S SS Hassan Rohayanti R Hassan Wan Haslina WH Muhammadsharif Fahmi F FF Latiff Liza Abdul LA

PloS one 20210128 1

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 da ...[more]

PMID: 33507983

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