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      SPEX 2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images

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      , , *
      Bioinformatics
      Oxford University Press

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          Abstract

          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 SPEX 2, 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@ 123456cs.cmu.edu

          Supplementary information: Supplementary data are avilable at Bioinformatics online.

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          Most cited references35

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          LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
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            Object recognition from local scale-invariant features

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              Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae.

              We have analyzed the translational status of each mRNA in rapidly growing Saccharomyces cerevisiae. mRNAs were separated by velocity sedimentation on a sucrose gradient, and 14 fractions across the gradient were analyzed by quantitative microarray analysis, providing a profile of ribosome association with mRNAs for thousands of genes. For most genes, the majority of mRNA molecules were associated with ribosomes and presumably engaged in translation. This systematic approach enabled us to recognize genes with unusual behavior. For 43 genes, most mRNA molecules were not associated with ribosomes, suggesting that they may be translationally controlled. For 53 genes, including GCN4, CPA1, and ICY2, three genes for which translational control is known to play a key role in regulation, most mRNA molecules were associated with a single ribosome. The number of ribosomes associated with mRNAs increased with increasing length of the putative protein-coding sequence, consistent with longer transit times for ribosomes translating longer coding sequences. The density at which ribosomes were distributed on each mRNA (i.e., the number of ribosomes per unit ORF length) was well below the maximum packing density for nearly all mRNAs, consistent with initiation as the rate-limiting step in translation. Global analysis revealed an unexpected correlation: Ribosome density decreases with increasing ORF length. Models to account for this surprising observation are discussed.
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                Author and article information

                Journal
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 June 2010
                1 June 2010
                1 June 2010
                : 26
                : 12
                : i47-i56
                Affiliations
                School of Computer Science, Carnegie Mellon Unversity, Pittsburgh, PA, USA
                Author notes
                * To whom correspondence should be addressed.
                Article
                btq172
                10.1093/bioinformatics/btq172
                2881357
                20529936
                45a448b4-ca9d-4fe9-b9c0-db6fc2f75f3f
                © The Author(s) 2010. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Categories
                Ismb 2010 Conference Proceedings July 11 to July 13, 2010, Boston, Ma, Usa
                Original Papers
                Bioimaging

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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