AltWOA

AltWOA performs feature selection on high-dimensional DNA microarray gene expression datasets using an altruistic variant of the Whale Optimization Algorithm to identify relevant biomarker genes.

Key Features:

• Altruistic Whale Optimization Algorithm: Extends the Whale Optimization Algorithm (WOA) by incorporating altruistic behavior among candidate solutions to improve convergence toward optimal feature subsets.
• High-Dimensional Feature Selection: Selects informative genes from large DNA microarray gene expression datasets while eliminating non-informative features.
• Meta-Heuristic Optimization: Applies a population-based meta-heuristic search strategy to explore complex feature spaces and identify optimal gene subsets.

Scientific Applications:

• Biomarker Discovery: Identifies disease-associated genes in DNA microarray datasets.
• Cancer Genomics: Detects gene expression features associated with different cancer types.
• High-Dimensional Data Analysis: Supports dimensionality reduction and feature selection in genomic datasets.

Methodology:

AltWOA models the bubble-net feeding behavior of humpback whales through the Whale Optimization Algorithm and introduces altruistic interactions among candidate solutions to propagate promising feature subsets during optimization.