ArticlePloS one2021
HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Deep learning assisted cancer disease prediction from gene expression data using WT-GAN.BMC medical informatics and decision making · 2024Article
- Use of relevancy and complementary information for discriminatory gene selection from high-dimensional gene expression data.PloS one · 2021Article
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Authors and funding
5 authors.
Funding
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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.
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