Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/17808
Title: [PDF] from researchgate.net Classification of colorectal carcinogenic tissue with different dna chip technologies
Authors: Simjanoska, Monika
Madevska Bogdanova, Ana
Popeska, Zaneta
Keywords: DNA microarray, Illumina, Affymetrix, machine learning, colorectal cancer, Bayes’ theorem, posterior probability, Support Vector Machines.
Issue Date: 8-May-2013
Conference: the 6th International Conference on Information Technology, ser. ICIT
Abstract: We explore increased or decreased colorectal gene expression levels since they are the reason for improper work of the cells in the colorectal region, i.e. the processes they are associated with are disrupted. In the previous work, we have unveiled the genes responsible for the colorectal cancer occurrence (the biomarkers), and made a model for classification which determines whether one patient is carcinogenic. The model uses a developed methodology that calculates the Bayesian posterior probability for classification. The gene expression profiling was done by using the DNA microarray technology from the Illumina microarray technology. The motivation of this research is the comparation between the two different DNA chip technologies, Illumina and Affymetrix, which misses in the literature, especially for the problem of colorectal cancer classification. We examined the gene expression data obtained from the Affymetrix, in order to analyze the differences in the classification process.
URI: http://hdl.handle.net/20.500.12188/17808
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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