Evolving Coherent and Non-trivial Biclusters from Gene Expression Data: An Evolutionary Approach

被引：0

作者：

Mukhopadhyay, Anirban ^{[1
]}

Maulik, Ujjwal ^{[2
]}

Bandyopadhyay, Sanghamitra ^{[3
]}

机构：

[1] Univ Kalyani, Dept Comp Sci & Engg, Kalyani 741235, W Bengal, India

[2] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, W Bengal, India

[3] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, W Bengal, India

来源：

2008 IEEE REGION 10 CONFERENCE: TENCON 2008, VOLS 1-4 | 2008年

关键词：

Biclustering; mean squared residue; row variance; genetic algorithm;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Biclustering in microarray data is used to discover a set of genes expressed similarly in a subset of conditions. Biclustering algorithms require to identify coherent and non-trivial biclusters, i.e., the biclusters should have low mean squared residue and high row variance. This article presents a genetic algorithm based biclustering technique that optimizes a combination of these objectives. A novel encoding strategy is proposed. The performance of the proposed algorithm has been evaluated on two benchmark real life gene expression data sets and compared with some other well-known biclustering techniques.

引用

页码：2471 / +

页数：2

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