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...

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Vydané v:	Scientific African Ročník 23; s. e02012
Hlavní autori:	Adebayo, Paul Olujide, Jimoh, Rasheed Gbenga, Yahya, Waheed Babatunde
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.03.2024 Elsevier
Predmet:	Biomarker discovery Computational efficiency Data-driven threshold Fuzzy particle swarm optimization Gene expression Gene selection Microarrays Biomarker discovery Data-driven threshold Microarrays Fuzzy particle swarm optimization Gene selection Computational efficiency Gene expression
ISSN:	2468-2276, 2468-2276
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