ArticleScientific reports2023
A new hybrid algorithm for three-stage gene selection based on whale optimization.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- An improved sparrow search algorithm and its application in the deployment of 3D wireless sensor nodes.Scientific reports · 2025Article
- Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies.Scientific reports · 2025Article
- Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification.MethodsX · 2025Article
- Advances in Zeroing Neural Networks: Bio-Inspired Structures, Performance Enhancements, and Applications.Biomimetics (Basel, Switzerland) · 2025Review
- Enhancing load frequency control and automatic voltage regulation in Interconnected power systems using the Walrus optimization algorithm.Scientific reports · 2024Article
- Leveraging enhanced egret swarm optimization algorithm and artificial intelligence-driven prompt strategies for portfolio selection.Scientific reports · 2024Article
- PMScientific reports · 2024Article
- An improved equilibrium optimization algorithm for feature selection problem in network intrusion detection.Scientific reports · 2024Article
- A Survey on Biomimetic and Intelligent Algorithms with Applications.Biomimetics (Basel, Switzerland) · 2024Article
- Intelligent mutation based evolutionary optimization algorithm for genomics and precision medicine.Functional & integrative genomics · 2024Article
- The prediction of Chongqing's GDP based on the LASSO method and chaotic whale group algorithm-back propagation neural network-ARIMA model.Scientific reports · 2023Article
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Authors and funding
8 authors.
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Abstract
In biomedical data mining, the gene dimension is often much larger than the sample size. To solve this problem, we need to use a feature selection algorithm to select feature gene subsets with a strong correlation with phenotype to ensure the accuracy of subsequent analysis. This paper presents a new three-stage hybrid feature gene selection method, that combines a variance filter, extremely randomized tree, and whale optimization algorithm. First, a variance filter is used to reduce the dimension of the feature gene space, and an extremely randomized tree is used to further reduce the feature gene set. Finally, the whale optimization algorithm is used to select the optimal feature gene subset. We evaluate the proposed method with three different classifiers in seven published gene expression profile datasets and compare it with other advanced feature selection algorithms. The results show that the proposed method has significant advantages in a variety of evaluation indicators.
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