Li-Juan Zhang, National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
Huo-Wang Chen, National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
Jian Wen, National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method.
Citation:
Li-Juan Zhang, Zhou-Jun Li, Huo-Wang Chen, Jian Wen, "Minimum Redundancy Gene Selection Based on Grey Relational Analysis," icdmw, pp.120-124, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006