Hybrid particle swarm optimization and tabu search approach for selecting genes for tumor classification using gene expression data

DOI10.1016/j.compbiolchem.2007.10.001zbMath1142.92020OpenAlexW50145612WikidataQ31140584 ScholiaQ31140584MaRDI QIDQ936035

Wei Kong, Qi Shen, Wei-Min Shi

Publication date: 12 August 2008

Published in: Computational Biology and Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.compbiolchem.2007.10.001

zbMATH Keywords

tabu searchgene expression dataparticle swarm optimizationgene selection

Mathematics Subject Classification ID

Medical applications (general) (92C50) Biochemistry, molecular biology (92C40) Computational methods for problems pertaining to biology (92-08)

Related Items (5)

Particle swarm optimization: Hybridization perspectives and experimental illustrations ⋮ Computational optimization for S-type biological systems: cockroach genetic algorithm ⋮ A novel weighted support vector machine based on particle swarm optimization for gene selection and tumor classification ⋮ An improved particle swarm optimization algorithm based on centroid and exponential inertia weight ⋮ A constructive data classification version of the particle swarm optimization algorithm

Uses Software

• HykGene

Cites Work

• Future paths for integer programming and links to artificial intelligence
• Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models
• Selection bias in gene extraction on the basis of microarray gene-expression data
• Gene selection for cancer classification using support vector machines

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