Swathypriyadharsini P1,∗, K.Premalatha2,†
Computer Systems Science and Engineering, Vol.35, No.1, pp. 39-50, 2020, DOI:10.32604/csse.2020.35.039
Abstract Microarrays have reformed biotechnological research in the past decade. Deciphering the hidden patterns in gene expression data proffers a prodigious
preference to strengthen the understanding of functional genomics. The complexity of biological networks with larger volume of genes also increases the
challenges of comprehending and interpretation of the resulting mass of data. Clustering addresses these challenges, which is essential in the data mining
process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be
useful in making known the natural structure inherent in gene expression data, understanding… More >
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