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R.Jumali_S.Deris_S.Z.M.Hashim_M.F.Misman_M.S._Mohamad2009-A_Study_of_Network-based_Approach_for_Cancer_Classification.pdf
A Study of Network-based Approach for Cancer Classification
<p> The advent of high-throughput techniques such as</p>
<div>microarray data enabled researchers to elucidate process in a</div>
<div>cell that fruitfully useful for pathological and medical. For</div>
<div>such opportunities, microarray gene expression data have been</div>
<div>explored and applied for various types of studies e.g. gene</div>
<div>association, gene classification and construction of gene</div>
<div>network. Unfortunately, since gene expression data naturally</div>
<div>have a few of samples and thousands of genes, this leads to a</div>
<div>biological and technical problems. Thus, the availability of</div>
<div>artificial intelligence techniques couples with statistical</div>
<div>methods can give promising results for addressing the</div>
<div>problems. These approaches derive two well known methods:</div>
<div>supervised and unsupervised. Whenever possible, these two</div>
<div>superior methods can work well in classification and clustering</div>
<div>in term of class discovery and class prediction. Significantly, in</div>
<div>this paper we will review the benefit of network-based in term</div>
<div>of interaction data for classification in identification of class</div>
<div>cancer.</div>
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Mohd Saberi
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2012-05-11 01:49:20 UTC
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