基因表达数据中局部模式的查询

基因表达数据分析一般是通过挖掘局部模式来实现的。保序子矩阵是局部模式挖掘中一种经典的模型,可以获取到在若干条件下表现出一致趋势的一组基因。高通量基因微阵列技术的进步,促进了海量基因表达数据的产生,使得对高性能基因表达数据分析算法的需求极为迫切。现有方法大多数是通过批量挖掘的方法来分析数据,即使有通过查询方式来获取精确结果的方法,其全面性与性能也有待提高。为了提高数据分析的效率与准确性,首先提出一种基于前缀树的基因表达数据索引gIndex,然后给出了一种基于列关键词查询的保序子矩阵分析方法GEQ_c。其不经过批量挖掘,只需要建立索引并通过关键词来完成正相关/负相关/时滞等模式的查询。实验结果表明,与现有方法相比,所提算法具有良好的数据分析效率与可扩展性。

Local Pattern Query from Gene Expression Data

Local pattern mining plays an important role in gene expression data analysis.One classical model in local pattern mining is order-preserving subMatrix (OPSM),which captures the general tendency of subset of genes in subset of conditions.With the development of high-throughput gene microarray techniques,it produces massive of gene expression datasets.In this situation,it is urgent to design high performance algorithms.Most of the existing methods are batch mining technique,even though it can be addressed by query method,the comprehensiveness and behaviors still should be improved.To make data analysis efficient and accurate,we first proposed a prefix-tree based indexing method for gene expression data,then gave a column keyword based OPSM query methods.It uses index and search method instead of batch mining to query positive,negative and time-delayed OPSMs.We conducted extensive experiments and compared our method with existing methods.The experimental results demonstrate that the proposed method is efficient and scalable.