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논문검색

Gene Expression Analysis

원문정보

초록

영어

In the past decade rapid advances of microarray technologies have made it possible to monitor the expression profiles of thousands of genes under various experimental conditions. The requirements for methods to handle such amounts of data have arisen. These massive source of information extracted from the genome project contain the keys to address fundamental problems relating to the prevention and cure of diseases, biological evolution mechanisms and the understanding of particular functional elements in the human organism. The knowledge of the coding sequences of virtually every gene in an organism is an exciting opportunity to develop methods to study the role of a gene in a specific organism or biological function. One of such methods consists of the monitoring of the level of expression of a gene. It has been shown that specific patterns of gene expression occur during different biological states such as cell development and during normal physiological responses in tissues and cells. There are many data mining techniques which help to analyze the gene expression data. This paper discusses some of these methods adopted by different researchers.

목차

Abstract
 1. Introduction
 2. Clustering of Genes
 3. Classification of Genes
 4. Neural Networks
 5. Microarray Data
 References

저자정보

  • R. Radha Assistant Professor, Department of Computer Science, S.D.N.B.Vaishnav College for Women, Chromepet

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