A fast algorithm on detecting spatially locally co-ezPressed regions between genes from in situ hybridization data

摘要：

BackgroundHigh-dimensional, high-resolution gene expression data generated by in situ hybridization is useful tool in functional genomics. A challenge here is how to efficiently detect local co-expression patterns between genes. Here we present an algorithm that efficiently detects the local co-expressed regions.Data & MethodsThe data from Figure 3B of Carson et ai. 1 is used to demonstrate the usefulness of our algorithm. This dataset involves several genes expressed in the mouse brain region known as substantia nigra. A 0-1 matrix is used to represent the co-expression matrix where 1 means two genes are both expressed at a given pixel.

作者: Xiaotu Ma Wenyuan Li

作者单位: Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China, 200240 Mole Molecular and Computational Biology Program, Department of Biological Sciences, University of Southe

会议类型: 国际会议

会议名称: The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)

会议地点: 北京

会议语种:英文

页码: 852

在线出版日期: 2009-01-01（万方平台首次上网日期，不代表论文的发表时间）