HybridGWOSPEA2ABC: a novel feature selection algorithm for gene expression data analysis and cancer classification
The novel hybridization algorithm enhances performance by maintaining solution diversity, efficiently converging to optimal solutions, and improving the exploration and exploitation of the search space. This study provides a better understanding of relevant genes for cancer classification and promotes effective methodologies for disease detection and classification.
Authors
- Thipendra P. Singh (ORCID: https://orcid.org/0000-0002-9991-6494)
- Ashimjyoti Nath (ORCID: https://orcid.org/0009-0009-7749-0427)
- Sanjib Kr. Kalita (ORCID: https://orcid.org/0000-0002-0576-3010)
- Chandan Jyoti Kumar (ORCID: https://orcid.org/0000-0003-3160-9217)
- Renu Dhir (ORCID: https://orcid.org/0000-0003-1641-2619)
Institutions
- Gauhati University (IN)
- Bennett University (IN)
- Cotton University (IN)
- Dr. B. R. Ambedkar National Institute of Technology Jalandhar (IN)
Publication Details
- Journal
- Computer Methods in Biomechanics & Biomedical Engineering
- Published
- 2025-04-26
- DOI
- https://doi.org/10.1080/10255842.2025.2495248
- Citations
- 3
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 2.42