Biclustering Analysis on Class Discovery From Gene Expression Data

被引：0

作者：

Anitha, S. ^{[1
]}

Chandran, C. P. ^{[2
]}

机构：

[1] Bharathiar Univ, Coimbatore, Tamil Nadu, India

[2] Ayya Nadar Janaki Ammal Coll, Comp Sci, Sivakasi, India

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATIONS TECHNOLOGIES (ICCCT 15) | 2015年

关键词：

Data Mining; Biclustering; Gene Expression Data;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The objective of this work "Biclustering Analysis on Class Discovery from Gene Expression Data", is to analysis biclustering techniques of data mining to create new algorithm and to improve the existing algorithm in order to apply them to some of the issues in Gene Expression Data such as Class Discovery to minimize the complexities involved in providing solutions to them. In this work an algorithm is proposed Enhanced Coupled Two-Way Clustering Algorithm (ECTWCA) for Class Discovery from Gene Expression Data. Biclustering approaches adopted in this work identifies coherent patterns known as scaling and shifting patterns from high dimensional Gene Expression Data.

引用

页码：55 / 60

页数：6

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