SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images.
SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images.
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DOI：
10.1093/bioinformatics/btq172
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发表时间：
2010-06-15
期刊：
影响因子：
--
通讯作者：
Xing EP
中科院分区：
文献类型：
--
作者：
Puniyani K;Faloutsos C;Xing EP
动机：mRNA丰度的微阵列分析通常适合于果蝇等多细胞生物中基因表达的临时分析。开发准确和自动的图像分析系统，以促进复杂的临时 - 空间mRNA模式的有效挖掘，这对于功能基因组学和网络推断至关重要在更高的生物体中。
结果：我们提出了一种用于胚胎图像处理的自动系统，可以在果蝇胚胎中提取，转换，比较，分类和聚类空间基因表达模式。基因表达。我们对果蝇图像的最大公开收集进行了实验自动图像注释，并且还发现了基因本体学功能注释的簇，以及来自人类策展人使用的受控词汇的注释项，以描述这些图像。
可用性：软件将在http://www.sailing.cs.cmu.edu/上找到。
联系人：epxing@cs.cmu.edu
补充信息：在线生物信息学上可以避免补充数据。
Motivation: Microarray profiling of mRNA abundance is often ill suited for temporal–spatial analysis of gene expressions in multicellular organisms such as Drosophila. Recent progress in image-based genome-scale profiling of whole-body mRNA patterns via in situ hybridization (ISH) calls for development of accurate and automatic image analysis systems to facilitate efficient mining of complex temporal–spatial mRNA patterns, which will be essential for functional genomics and network inference in higher organisms. Results: We present SPEX2, an automatic system for embryonic ISH image processing, which can extract, transform, compare, classify and cluster spatial gene expression patterns in Drosophila embryos. Our pipeline for gene expression pattern extraction outputs the precise spatial locations and strengths of the gene expression. We performed experiments on the largest publicly available collection of Drosophila ISH images, and show that our method achieves excellent performance in automatic image annotation, and also finds clusters that are significantly enriched, both for gene ontology functional annotations, and for annotation terms from a controlled vocabulary used by human curators to describe these images. Availability: Software will be available at http://www.sailing.cs.cmu.edu/ Contact: epxing@cs.cmu.edu Supplementary information: Supplementary data are avilable at Bioinformatics online.
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DOI：
10.1111/1467-9868.00346
发表时间：
2002-01-01
影响因子：
5.8
作者：
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通讯作者：
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DOI：
10.1073/pnas.0901910106
发表时间：
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影响因子：
11.1
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DOI：
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发表时间：
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期刊：
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影响因子：
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作者：
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作者：
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