Hybridization of data-driven threshold algorithm with fuzzy particle swarm optimization technique for gene selection in microarray data

Hybridization of data-driven threshold algorithm with fuzzy particle swarm optimization technique for gene selection in microarray data

Microarrays have revolutionized genomics by enabling the simultaneous measurement of thousands of gene expressions. However, the high dimensionality of microarray data poses challenges in identifying relevant genes for disease diagnosis and biomarker discovery. This article introduces a novel hybrid...

Full description

Bibliographic Details
Main Authors: Paul Olujide Adebayo, Rasheed Gbenga Jimoh, Waheed Babatunde Yahya
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Scientific African
Subjects:
Microarrays
Gene selection
Gene expression
Fuzzy particle swarm optimization
Computational efficiency
Biomarker discovery
Online Access:http://www.sciencedirect.com/science/article/pii/S2468227623004660

Internet

http://www.sciencedirect.com/science/article/pii/S2468227623004660

Similar Items