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    ABSTRACT: Invited Review Abstract: Super-resolution microscopy is one of the advanced means for the study of life sciences. The 2014 Nobel prize in Chemistry was awarded to three scientists for their contributions to the super-resolution microscopy. Representative techniques achieving super-resolution are stimulated-emission, structured-illumination, and singlemolecule localization. The advancement of these techniques enable the visualization of the detail in cell organelle, macromolecules, and the localization of molecules. Such kind of information was unresolvable under traditional optical microscopes and will help understand the structure, location, interaction of molecules within cells in nanometer scale.
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    ABSTRACT: Traditionally, gene expression measurements were performed on "bulk" samples containing populations of thousands of cells. Recent advances in genomic technology have made it possible to measure gene expression in hundreds of individual cells at a time. As a result, cellular properties that were previously masked in "bulk" measurements can now be observed directly. In this review, we will survey emerging technologies for single cell transcriptomics, and describe how they are used to study complex disease such as cancer, as well as other biological phenomena such as tissue regeneration, embryonic development, and immune response.
    Frontiers in Oncology 03/2015; 5:53. DOI:10.3389/fonc.2015.00053
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    ABSTRACT: Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 to 1000 unique RNA species in hundreds of individual cells. Correlation analysis of the ~10(4) to 10(6) pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins. Copyright © 2015, American Association for the Advancement of Science.
    Science 04/2015; 348(6233). DOI:10.1126/science.aaa6090 · 31.48 Impact Factor