GINI: From ISH Images to Gene Interaction Networks

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چکیده

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GINI: From ISH Images to Gene Interaction Networks

Accurate inference of molecular and functional interactions among genes, especially in multicellular organisms such as Drosophila, often requires statistical analysis of correlations not only between the magnitudes of gene expressions, but also between their temporal-spatial patterns. The ISH (in-situ-hybridization)-based gene expression micro-imaging technology offers an effective approach to ...

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Spatiotemporal Gene Networks from ISH Images

As large-scale techniques for studying and measuring gene expressions have been developed, automatically inferring gene interaction networks from expression data has emerged as a popular technique to advance our understanding of cellular systems. Accurate prediction of gene interactions, especially in multicellular organisms such as Drosophila or humans, requires temporal and spatial analysis o...

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Inferring Gene Interaction Networks from ISH Images via Kernelized Graphical Models

New bio-technologies are being developed that allow highthroughput imaging of gene expressions, where each image captures the spatial gene expression pattern of a single gene in the tissue of interest. This paper addresses the problem of automatically inferring a gene interaction network from such images. We propose a novel kernel-based graphical model learning algorithm, that is both convex an...

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SPEX: Automated Concise Extraction of Spatial Gene Expression Patterns from Fly Embryo ISH Images

NETWORK ANALYSIS Using the features extracted as described in the main text, we constructed a gene regulatory network, using only spatial correlations. The images from the BDTNP project were converted into features, as discussed, and all the expression patterns obtained for a single gene were averaged to compute a mean expression pattern per gene. We constructed two sets of experiments. In the ...

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SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images

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 tem...

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ژورنال

عنوان ژورنال: PLoS Computational Biology

سال: 2013

ISSN: 1553-7358

DOI: 10.1371/journal.pcbi.1003227