Visualization of image data from cells to organisms

By Thomas Walter, David W. Shattuck, Richard Baldock, Mark E. Bastin, Anne E Carpenter, Suzanne Duce, Jan Ellenberg, Adam Fraser, Nicholas Hamilton, Steve Pieper and 4 more. Nature Methods, 2010

987 citations recorded by the source corpus.

Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/333f3f352ea27459ff4cfc0654d741949c93395e

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Citations in the corpus

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De novo assembly of bacterial transcriptomes from RNA-seq data (2015, background): “…transcriptome assembly remains a challenging problem owing to a variety of factors, including artifacts from library construction, errors in sequencing, variable intra-read and inter-read error rates, repeat sequences, and transcript expression ranges that span several orders of magnitude [3].”
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High‐throughput DNA sequencing – concepts and limitations (2010, background): “Given the immense diversity, we have not discussed these applications in depth here; other reviews with a stronger focus on specific applications and data analysis are available [24, 82–88].”
Visualization of omics data for systems biology (2010, methodology): “Fulfilling this ambitious goal requires still further development in visualization methods; in particular, better integration with visualization of other kinds of data, such as imaging dat”
Game On, Science - How Video Game Technology May Help Biologists Tackle Visualization Challenges (2013, background): “Biology currently undergoes a rapid expansion, calling for tools to visualize huge and complex systems, such as macromolecular structures, -omics networks or even organs and organisms [1–3].”
Phenomics: the next challenge (2010, background): “Imaging is ideal for phenomic studies owing to the availability of many technologies that span molecular to organismal spatial scale”
Field guide to next‐generation DNA sequencers (2011, methodology): “…molecule, Illumina data can be used for de novo assemblies [e.g. Li et al. 2009 (but see Worley & Gibbs 2010); Paszkiewicz & Studholme 2010], especially when supplemented with mate-paired reads (Gnerre et al. 2011), and ⁄ or data from one of the longerread platforms (e.g. Dalloul et al. 2010).”
Future challenges in cephalopod research* (2014, methodology): “Furthermore, non-invasive scanning techniques such as magnetic resonance imaging (MRI), computed tomography (CT), or micro-computed tomography (mCT) now allow analysing whole specimens from the millimetre to the metre scale (Walter et al., 2010).”
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3D Slicer as an Image Computing Platform for the Quantitative Imaging Network (2012, neutral): “Several other tools, such as OsiriX [26], BioImage Suite, MIPAV [27] and ImageJ [28], are similar to Slicer in that they provide extensible development platforms for biomedical imaging applications (for a comprehensive comparison of these tools we refer the reader to the earlier surveys [29,30]).”