Imaging: Deep learning improves image analysis (English)
In:
Nature methods
;
14
, 6
; 556
;
2017
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ISSN:
- Article (Journal) / Print
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Title:Imaging: Deep learning improves image analysis
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Published in:Nature methods ; 14, 6 ; 556
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Publisher:
- New search for: Nature Publishing Group
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Place of publication:New York, NY
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Publication date:2017
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ISSN:
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ZDBID:
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DOI:
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Type of media:Article (Journal)
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Type of material:Print
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Language:English
- New search for: 42.03 / 42.03 / 35.07 / 35.07
- Further information on Basic classification
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Source:
Table of contents – Volume 14, Issue 6
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 541
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CRISPR standards| 2017
- 543
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The Author File: Yannick DoyonVivien Marx et al. | 2017
- 545
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Points of Significance: ClusteringNaomi Altman et al. | 2017
- 547
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Unexpected mutations after CRISPR-Cas9 editing in vivoKellie A Schaefer et al. | 2017
- 548
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Digenome-seq web tool for profiling CRISPR specificityJeongbin Park et al. | 2017
- 549
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E-scape: interactive visualization of single-cell phylogenetics and cancer evolutionMaia A Smith et al. | 2017
- 551
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Biochemistry: GPCR interactions in space and timeAllison Doerr et al. | 2017
- 552
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Sensors and probes: CRISPR's paper testTal Nawy et al. | 2017
- 552
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Microscopy: Good vibrations for super-multiplexed imagingRita Strack et al. | 2017
- 554
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Stem cells: Extending pluripotency with a cocktailIrene Jarchum et al. | 2017
- 555
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Microscopy: Chip-based nanoscopy| 2017
- 555
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Sequencing: Single genome amplification goes linear| 2017
- 555
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Synthetic biology: Engineering complex and robust genetic circuits| 2017
- 555
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Imaging: Track first and identify later| 2017
- 556
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Imaging: Deep learning improves image analysis| 2017
- 556
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Molecular biology: Building a better TRAP for translation| 2017
- 556
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Neuroscience: Electrophysiology in intact Caenorhabditis elegans| 2017
- 556
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Structural biology: GPCR function insights by cryo-EM| 2017
- 557
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Neuroscience: Microfetti: a fate-mapping system for microgliaKate Gao et al. | 2017
- 559
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Organoids: a better in vitro modelKatherine Ellen Foley et al. | 2017
- 563
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Cas9 in action: no more known unknowns?Fyodor D Urnov et al. | 2017
- 565
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Normalizing single-cell RNA sequencing data: challenges and opportunitiesCatalina A Vallejos et al. | 2017
- 573
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Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactionsJohn Paul Shen et al. | 2017
- 577
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Genetic interaction mapping in mammalian cells using CRISPR interferenceDan Du et al. | 2017
- 581
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Large-field-of-view imaging by multi-pupil adaptive opticsJung-hoon Park et al. | 2017
- 584
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SCnorm: robust normalization of single-cell RNA-seq dataRhonda Bacher et al. | 2017
- 587
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ModelFinder: fast model selection for accurate phylogenetic estimatesSubha Kalyaanamoorthy et al. | 2017
- 590
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Genome-wide profiling of heritable and de novo STR variationsThomas Willems et al. | 2017
- 593
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Iterative expansion microscopyJae-byum Chang et al. | 2017
- 600
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Mapping the genomic landscape of CRISPR-Cas9 cleavagePeter Cameron et al. | 2017
- 607
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CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targetsShengdar Q Tsai et al. | 2017
- 615
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Marker-free coselection for CRISPR-driven genome editing in human cellsDaniel Agudelo et al. | 2017
- 621
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Generation of pure GABAergic neurons by transcription factor programmingNan Yang et al. | 2017
- 629
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A tiling-deletion-based genetic screen for cis-regulatory element identification in mammalian cellsYarui Diao et al. | 2017