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Special Feature: Method of the Year 2017 Organoids: the body builders pp19 - 22 Michael Eisenstein doi:10.1038/nmeth.4538 |
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Primer | Top |
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Special Feature: Method of the Year 2017 Organoids p23 Natalie de Souza doi:10.1038/nmeth.4576 A brief overview of stem cell-derived organoids: how they are made and what the challenges are. |
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Commentaries | Top |
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Special Feature: Method of the Year 2017 Imaging organoids: a bright future ahead pp24 - 26 Anne C Rios and Hans Clevers doi:10.1038/nmeth.4537 |
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Special Feature: Method of the Year 2017 Organoids required! A new path to understanding human brain development and disease pp27 - 29 Paola Arlotta doi:10.1038/nmeth.4557 |
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Methods to Watch | Top |
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Special Feature: Method of the Year 2017 Spatial transcriptomics p30 Tal Nawy doi:10.1038/nmeth.4542 It will soon be commonplace to localize gene expression in tissues. |
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Special Feature: Method of the Year 2017 Structure via super-resolution p30 Natalie de Souza doi:10.1038/nmeth.4543 Fluorescence nanoscopy is extending its reach into structural biology. |
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Special Feature: Method of the Year 2017 Towards a dynamic 3D genome p31 Nicole Rusk doi:10.1038/nmeth.4544 Sequencing and imaging bring unique aspects to genome architecture. |
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Special Feature: Method of the Year 2017 Transformative electrophysiology p31 Nina Vogt doi:10.1038/nmeth.4545 Increases in throughput push electrophysiology into a new era. |
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Special Feature: Method of the Year 2017 Mass spectrometry imaging takes off p32 Allison Doerr doi:10.1038/nmeth.4546 Recent advances in mass spectrometry imaging enable label-free molecular mapping in single cells and in 3D. |
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Special Feature: Method of the Year 2017 Tracing cellular descent p32 Tal Nawy doi:10.1038/nmeth.4547 Sophisticated barcoding approaches are transforming cell lineaging. |
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Special Feature: Method of the Year 2017 The new XFELs p33 Allison Doerr doi:10.1038/nmeth.4548 New X-ray free-electron (XFEL) facilities will broaden access to this technology, facilitate methods development, and push boundaries in structural biology. |
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Special Feature: Method of the Year 2017 Machine learning in neuroscience p33 Nina Vogt doi:10.1038/nmeth.4549 In the era of big data, neuroscience can profit from deep-learning approaches. |
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Technology Feature | Top |
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Chemical biology: fats as research subjects pp35 - 38 Vivien Marx doi:10.1038/nmeth.4550 Fats add structure, they signal, they interact. In the lab, lipids are tough to work with but worth the challenge. |
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Resources | Top |
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Multicolor quantitative confocal imaging cytometry pp39 - 46 Daniel L Coutu, Konstantinos D Kokkaliaris, Leo Kunz and Timm Schroeder doi:10.1038/nmeth.4503 This resource paper describes the steps involved in carrying out quantitative multicolour imaging in tissue. It is applied to cleared mouse bone and plots the spatial distribution of specific cell populations within the marrow. |
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Systematic characterization of maturation time of fluorescent proteins in living cells pp47 - 51 Enrique Balleza, J Mark Kim and Philippe Cluzel doi:10.1038/nmeth.4509 This work characterizes the maturation kinetics of 50 cyan to far-red fluorescent proteins and provides evidence that proteins that mature faster than their brighter but slower counterparts are more useful for quantitative evaluation of fast processes. |
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Brief Communications | Top |
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Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics pp53 - 56 Zijuan Lai, Hiroshi Tsugawa, Gert Wohlgemuth, Sajjan Mehta, Matthew Mueller et al. doi:10.1038/nmeth.4512 An integrated cheminformatics workflow aids the functional and structural annotation of unknown metabolites found across multiple biological systems. |
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Programmable full-adder computations in communicating three-dimensional cell cultures pp57 - 60 David Ausländer, Simon Ausländer, Xavier Pierrat, Leon Hellmann, Leila Rachid et al. doi:10.1038/nmeth.4505 Designer cells executing rationally assembled genetic programs that can process input signals with programmable logic are combined in a 3D cell culture that performs three-input, two-output full-adder computations. |
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Articles | Top |
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NetSig: network-based discovery from cancer genomes pp61 - 66 Heiko Horn, Michael S Lawrence, Candace R Chouinard, Yashaswi Shrestha, Jessica Xin Hu et al. doi:10.1038/nmeth.4514 NetSig is a network-based statistic that identifies cancer driver genes with high accuracy and can be combined with gene-based statistical tests; results are validated with a large-scale in vivo tumorigenesis assay. |
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PDB-wide identification of biological assemblies from conserved quaternary structure geometry pp67 - 72 Sucharita Dey, David W Ritchie and Emmanuel D Levy doi:10.1038/nmeth.4510 Monomeric and homo-oligomeric protein quaternary structure states are predicted on a PDB-wide scale using a method that approaches the accuracy of manual annotation. |
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A permanent window for the murine lung enables high-resolution imaging of cancer metastasis pp73 - 80 David Entenberg, Sonia Voiculescu, Peng Guo, Lucia Borriello, Yarong Wang et al. doi:10.1038/nmeth.4511 The window for high-resolution imaging of the lung (WHRIL) enables longitudinal imaging of the same region of murine lung tissue over a period of weeks, and this enables the visualization of spontaneous cancer metastasis from the earliest stages. |
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An improved MS2 system for accurate reporting of the mRNA life cycle pp81 - 89 Evelina Tutucci, Maria Vera, Jeetayu Biswas, Jennifer Garcia, Roy Parker et al. doi:10.1038/nmeth.4502 An improved MS2-tagging system for live-cell RNA imaging allows faithful monitoring of the mRNA life cycle, overcoming degradation artifacts associated with previous versions and having implications regarding mRNA regulation in yeast. |
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