Filter
Associated Lab
- Ahrens Lab (30) Apply Ahrens Lab filter
- Aso Lab (29) Apply Aso Lab filter
- Baker Lab (19) Apply Baker Lab filter
- Betzig Lab (88) Apply Betzig Lab filter
- Beyene Lab (1) Apply Beyene Lab filter
- Bock Lab (14) Apply Bock Lab filter
- Branson Lab (38) Apply Branson Lab filter
- Card Lab (20) Apply Card Lab filter
- Cardona Lab (41) Apply Cardona Lab filter
- Chklovskii Lab (10) Apply Chklovskii Lab filter
- Clapham Lab (7) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (2) Apply Darshan Lab filter
- Dickson Lab (25) Apply Dickson Lab filter
- Druckmann Lab (21) Apply Druckmann Lab filter
- Dudman Lab (26) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (4) Apply Egnor Lab filter
- Fetter Lab (31) Apply Fetter Lab filter
- Fitzgerald Lab (7) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (15) Apply Funke Lab filter
- Gonen Lab (59) Apply Gonen Lab filter
- Grigorieff Lab (34) Apply Grigorieff Lab filter
- Hantman Lab (21) Apply Hantman Lab filter
- Harris Lab (37) Apply Harris Lab filter
- Heberlein Lab (13) Apply Heberlein Lab filter
- Hermundstad Lab (5) Apply Hermundstad Lab filter
- Hess Lab (47) Apply Hess Lab filter
- Huston Lab (4) Apply Huston Lab filter
- Jayaraman Lab (33) Apply Jayaraman Lab filter
- Ji Lab (33) Apply Ji Lab filter
- Johnson Lab (1) Apply Johnson Lab filter
- Karpova Lab (10) Apply Karpova Lab filter
- Keleman Lab (7) Apply Keleman Lab filter
- Keller Lab (56) Apply Keller Lab filter
- Koyama Lab (21) Apply Koyama Lab filter
- Lavis Lab (83) Apply Lavis Lab filter
- Lee (Albert) Lab (22) Apply Lee (Albert) Lab filter
- Lee (Tzumin) Lab (48) Apply Lee (Tzumin) Lab filter
- Leonardo Lab (18) Apply Leonardo Lab filter
- Lippincott-Schwartz Lab (52) Apply Lippincott-Schwartz Lab filter
- Liu Lab (35) Apply Liu Lab filter
- Looger Lab (114) Apply Looger Lab filter
- Magee Lab (31) Apply Magee Lab filter
- Menon Lab (12) Apply Menon Lab filter
- Murphy Lab (6) Apply Murphy Lab filter
- O'Shea Lab (1) Apply O'Shea Lab filter
- Pachitariu Lab (11) Apply Pachitariu Lab filter
- Pastalkova Lab (5) Apply Pastalkova Lab filter
- Pavlopoulos Lab (7) Apply Pavlopoulos Lab filter
- Podgorski Lab (12) Apply Podgorski Lab filter
- Reiser Lab (28) Apply Reiser Lab filter
- Riddiford Lab (20) Apply Riddiford Lab filter
- Romani Lab (20) Apply Romani Lab filter
- Rubin Lab (88) Apply Rubin Lab filter
- Saalfeld Lab (24) Apply Saalfeld Lab filter
- Scheffer Lab (32) Apply Scheffer Lab filter
- Schreiter Lab (35) Apply Schreiter Lab filter
- Simpson Lab (19) Apply Simpson Lab filter
- Singer Lab (35) Apply Singer Lab filter
- Spruston Lab (47) Apply Spruston Lab filter
- Stern Lab (46) Apply Stern Lab filter
- Sternson Lab (39) Apply Sternson Lab filter
- Stringer Lab (7) Apply Stringer Lab filter
- Svoboda Lab (115) Apply Svoboda Lab filter
- Tebo Lab (1) Apply Tebo Lab filter
- Tillberg Lab (4) Apply Tillberg Lab filter
- Tjian Lab (17) Apply Tjian Lab filter
- Truman Lab (53) Apply Truman Lab filter
- Turaga Lab (15) Apply Turaga Lab filter
- Turner Lab (11) Apply Turner Lab filter
- Wu Lab (8) Apply Wu Lab filter
- Zlatic Lab (27) Apply Zlatic Lab filter
- Zuker Lab (5) Apply Zuker Lab filter
Associated Project Team
- Fly Descending Interneuron (6) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (9) Apply Fly Functional Connectome filter
- Fly Olympiad (4) Apply Fly Olympiad filter
- FlyEM (50) Apply FlyEM filter
- FlyLight (24) Apply FlyLight filter
- GENIE (31) Apply GENIE filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (13) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (9) Apply Tool Translation Team (T3) filter
- Transcription Imaging (45) Apply Transcription Imaging filter
Associated Support Team
- Anatomy and Histology (13) Apply Anatomy and Histology filter
- Cell and Tissue Culture (9) Apply Cell and Tissue Culture filter
- Connectome Annotation (3) Apply Connectome Annotation filter
- Cryo-Electron Microscopy (20) Apply Cryo-Electron Microscopy filter
- Drosophila Resources (20) Apply Drosophila Resources filter
- Electron Microscopy (9) Apply Electron Microscopy filter
- Gene Targeting and Transgenics (9) Apply Gene Targeting and Transgenics filter
- Janelia Experimental Technology (26) Apply Janelia Experimental Technology filter
- Light Microscopy (4) Apply Light Microscopy filter
- Management Team (1) Apply Management Team filter
- Molecular Biology (8) Apply Molecular Biology filter
- Project Technical Resources (10) Apply Project Technical Resources filter
- Quantitative Genomics (15) Apply Quantitative Genomics filter
- Scientific Computing Software (49) Apply Scientific Computing Software filter
- Scientific Computing Systems (3) Apply Scientific Computing Systems filter
- Viral Tools (4) Apply Viral Tools filter
- Vivarium (5) Apply Vivarium filter
Publication Date
- 2021 (31) Apply 2021 filter
- 2020 (179) Apply 2020 filter
- 2019 (178) Apply 2019 filter
- 2018 (205) Apply 2018 filter
- 2017 (187) Apply 2017 filter
- 2016 (190) Apply 2016 filter
- 2015 (196) Apply 2015 filter
- 2014 (191) Apply 2014 filter
- 2013 (136) Apply 2013 filter
- 2012 (112) Apply 2012 filter
- 2011 (98) Apply 2011 filter
- 2010 (62) Apply 2010 filter
- 2009 (56) Apply 2009 filter
- 2008 (40) Apply 2008 filter
- 2007 (21) Apply 2007 filter
- 2006 (3) Apply 2006 filter
Tool Types
1885 Janelia Publications
Showing 1781-1790 of 1885 resultsWe built a digital nuclear atlas of the newly hatched, first larval stage (L1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. The atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a three-dimensional image of an L1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. This computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen.
Synaptic plasticity in adult neural circuits may involve the strengthening or weakening of existing synapses as well as structural plasticity, including synapse formation and elimination. Indeed, long-term in vivo imaging studies are beginning to reveal the structural dynamics of neocortical neurons in the normal and injured adult brain. Although the overall cell-specific morphology of axons and dendrites, as well as of a subpopulation of small synaptic structures, are remarkably stable, there is increasing evidence that experience-dependent plasticity of specific circuits in the somatosensory and visual cortex involves cell type-specific structural plasticity: some boutons and dendritic spines appear and disappear, accompanied by synapse formation and elimination, respectively. This Review focuses on recent evidence for such structural forms of synaptic plasticity in the mammalian cortex and outlines open questions.
Conditional expression of hairpin constructs in Drosophila is a powerful method to disrupt the activity of single genes with a spatial and temporal resolution that is impossible, or exceedingly difficult, using classical genetic methods. We previously described a method (Ni et al. 2008) whereby RNAi constructs are targeted into the genome by the phiC31-mediated integration approach using Vermilion-AttB-Loxp-Intron-UAS-MCS (VALIUM), a vector that contains vermilion as a selectable marker, an attB sequence to allow for phiC31-targeted integration at genomic attP landing sites, two pentamers of UAS, the hsp70 core promoter, a multiple cloning site, and two introns. As the level of gene activity knockdown associated with transgenic RNAi depends on the level of expression of the hairpin constructs, we generated a number of derivatives of our initial vector, called the "VALIUM" series, to improve the efficiency of the method. Here, we report the results from the systematic analysis of these derivatives and characterize VALIUM10 as the most optimal vector of this series. A critical feature of VALIUM10 is the presence of gypsy insulator sequences that boost dramatically the level of knockdown. We document the efficacy of VALIUM as a vector to analyze the phenotype of genes expressed in the nervous system and have generated a library of 2282 constructs targeting 2043 genes that will be particularly useful for studies of the nervous system as they target, in particular, transcription factors, ion channels, and transporters.
Real-time lineage tracing in flies gets a boost with three techniques to specifically label a progenitor’s daughter cells.
The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.
Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest.
In holometabolous insects, a species-specific size, known as critical weight, needs to be reached for metamorphosis to be initiated in the absence of further nutritional input. Previously, we found that reaching critical weight depends on the insulin-dependent growth of the prothoracic glands (PGs) in Drosophila larvae. Because the PGs produce the molting hormone ecdysone, we hypothesized that ecdysone signaling switches the larva to a nutrition-independent mode of development post-critical weight. Wing discs from pre-critical weight larvae [5 hours after third instar ecdysis (AL3E)] fed on sucrose alone showed suppressed Wingless (WG), Cut (CT) and Senseless (SENS) expression. Post-critical weight, a sucrose-only diet no longer suppressed the expression of these proteins. Feeding larvae that exhibit enhanced insulin signaling in their PGs at 5 hours AL3E on sucrose alone produced wing discs with precocious WG, CT and SENS expression. In addition, knocking down the Ecdysone receptor (EcR) selectively in the discs also promoted premature WG, CUT and SENS expression in the wing discs of sucrose-fed pre-critical weight larvae. EcR is involved in gene activation when ecdysone is present, and gene repression in its absence. Thus, knocking down EcR derepresses genes that are normally repressed by unliganded EcR, thereby allowing wing patterning to progress. In addition, knocking down EcR in the wing discs caused precocious expression of the ecdysone-responsive gene broad. These results suggest that post-critical weight, EcR signaling switches wing discs to a nutrition-independent mode of development via derepression.