The variable neighborhood search metaheuristic for fuzzy clusering cDNA microarray gene expression data

Nabil Belacel*, Miroslava Cuperlovic-Culf, Rodney Ouellette, Mohamed R. Boulassel

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

5 اقتباسات (Scopus)

ملخص

Several thousand genes can be monitored simultaneously using cDNA microarray technology. To exploit the huge amount of information contained in gene expression data, adaptation of existing and development of new computational methods are required. Recently, the Fuzzy C-Means (F-CM) method has been applied to cluster cDNA microarray data sets. To overcome some shortcomings of F-CM and to improve its performance, it was embedded into a variable neighborhood search (VNS) metaheuristic. The methodology was used to cluster four cDNA microarray data sets. Results show that VNS+F-CM substantially improves the findings obtained by F-CM. This methodology may yield significant benefit in the improvement of decision support systems used for gene expression classification.

اللغة الأصليةEnglish
عنوان منشور المضيفProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics)
المحررونM.H. Hamza
الصفحات51-56
عدد الصفحات6
حالة النشرPublished - 2004
منشور خارجيًانعم
الحدثProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics - Innsbruck, Austria
المدة: فبراير ١٦ ٢٠٠٤فبراير ١٨ ٢٠٠٤

سلسلة المنشورات

الاسمProceedings of the IASTED International Conference. Applied Informatics

Other

OtherProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics
الدولة/الإقليمAustria
المدينةInnsbruck
المدة٢/١٦/٠٤٢/١٨/٠٤

ASJC Scopus subject areas

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