Literature DB >> 18809490

Mapping the gene expression universe.

Eric Lécuyer1, Pavel Tomancak.   

Abstract

Methods to globally survey gene expression provide valuable insights into gene function during development. In particular, comprehensive in situ hybridization studies have demonstrated that gene expression patterns are extraordinarily diverse and new imaging techniques have been introduced to capture these patterns with higher resolution at the tissue, cellular, and subcellular levels. The analysis of massive image databases can be greatly facilitated by computer vision techniques once annotated image sets reach the crucial mass sufficient to train the computer in pattern recognition. Ultimately, genome-wide atlases of gene expression during development will record gene activity in living animals with at least cellular resolution and in the context of morphogenetic events. These emerging datasets will lead to great advances in the field of comparative genomics and revolutionize our ability to decipher and model developmental processes for a variety of organisms.

Mesh:

Year:  2008        PMID: 18809490     DOI: 10.1016/j.gde.2008.08.003

Source DB:  PubMed          Journal:  Curr Opin Genet Dev        ISSN: 0959-437X            Impact factor:   5.578


  6 in total

1.  Whole mount RNA fluorescent in situ hybridization of Drosophila embryos.

Authors:  Félix Legendre; Neal Cody; Carole Iampietro; Julie Bergalet; Fabio Alexis Lefebvre; Gaël Moquin-Beaudry; Olivia Zhang; Xiaofeng Wang; Eric Lécuyer
Journal:  J Vis Exp       Date:  2013-01-30       Impact factor: 1.355

Review 2.  Visualization of image data from cells to organisms.

Authors:  Thomas Walter; David W Shattuck; Richard Baldock; Mark E Bastin; Anne E Carpenter; Suzanne Duce; Jan Ellenberg; Adam Fraser; Nicholas Hamilton; Steve Pieper; Mark A Ragan; Jurgen E Schneider; Pavel Tomancak; Jean-Karim Hériché
Journal:  Nat Methods       Date:  2010-03       Impact factor: 28.547

3.  Analysis of cell fate from single-cell gene expression profiles in C. elegans.

Authors:  Xiao Liu; Fuhui Long; Hanchuan Peng; Sarah J Aerni; Min Jiang; Adolfo Sánchez-Blanco; John I Murray; Elicia Preston; Barbara Mericle; Serafim Batzoglou; Eugene W Myers; Stuart K Kim
Journal:  Cell       Date:  2009-10-30       Impact factor: 41.582

4.  Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval.

Authors:  Lei Yuan; Alexander Woodard; Shuiwang Ji; Yuan Jiang; Zhi-Hua Zhou; Sudhir Kumar; Jieping Ye
Journal:  BMC Bioinformatics       Date:  2012-05-23       Impact factor: 3.169

5.  A microfluidic device and computational platform for high-throughput live imaging of gene expression.

Authors:  Wolfgang Busch; Brad T Moore; Bradley Martsberger; Daniel L Mace; Richard W Twigg; Jee Jung; Iulian Pruteanu-Malinici; Scott J Kennedy; Gregory K Fricke; Robert L Clark; Uwe Ohler; Philip N Benfey
Journal:  Nat Methods       Date:  2012-09-30       Impact factor: 28.547

6.  A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis.

Authors:  Wenlu Zhang; Daming Feng; Rongjian Li; Andrey Chernikov; Nikos Chrisochoides; Christopher Osgood; Charlotte Konikoff; Stuart Newfeld; Sudhir Kumar; Shuiwang Ji
Journal:  BMC Bioinformatics       Date:  2013-12-28       Impact factor: 3.169

  6 in total

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