Rough Based Symmetrical Clustering for Gene Expression Profile Analysis

Identification of coexpressed genes is the central goal in microarray gene expression data analysis. Point symmetry-based clustering is an important unsupervised learning technique for recognizing symmetrical convex or non-convex shaped clusters. To enable fast automatic clustering of large microarr...

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Vydané v:	IEEE transactions on nanobioscience Ročník 14; číslo 4; s. 360 - 367
Hlavní autori:	Sarkar, Anasua, Maulik, Ujjwal
Médium:	Magazine Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2015
Predmet:	Algorithm design and analysis Automatic clustering algorithm Clustering algorithms Gene expression Indexes K-means algorithm Lungs microarray gene expression data Partitioning algorithms point-symmetry based distance Program processors rough set decision rules
ISSN:	1536-1241, 1558-2639
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