粗糙自组织映射在基因表达数据分析中的应用

Analyzing Gene Expression Data Based on Rough Self-organizing Maps

本文利用粗糙集与布尔逻辑离散约简算法改进了粗糙自组织映射算法,并应用于基因表达数据的分析中。算法改进了传统自组织映射收敛慢、网络规模难以确定的缺点,减小了网络规模不确定对分类效果的影响。使用酵母菌基因表达数据进行实验,得到了较好的网络质量、网络规模和分类效果,相比传统自组织映射使分类正确率提高了10.15%。

This paper presents an approach using rough set and Boolean reasoning discretization-reduction to improve the rough self-organizing maps, and using it to analyzz gene expression data. This approach can improve the conver-gence time and obtain the best map scale. We have tested the RSOM on the yeast data set, obtained better map quality and classification result.