A pipeline of image analysis and data mining tools for building the neuronal atlases of fruit fly brains.

<p>(a) A flowchart of the key steps in building a fruit fly brain atlas. (b) A 3D digital atlas of 269 stereotyped neurite tracts reconstructed from GAL4-label fruit fly brains <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Peng6" target="_blank">[19]</a>. Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.</p

Vaa3D visualization of 4D and 5D microscopic images, as well as associated 3D surface objects, of different model animals.

<p>(a) The hierarchical (multi-scale) 3D visualization of a fluorescent confocal image of fruit fly (<i>Drosophila melanogaster</i>) brain using both global and local 3D viewers. In the global viewer, different brain compartments rendered using surface meshes (in different colors) are overlaid on top of the 3D volume of a fruit fly brain. When an image is very large, the global viewer can serve for navigation purpose. A user can quickly define any 3D local region of interest and display it in a local 3D viewer using full resolution. In this example, the brain voxels can be rendered in a different color from the global viewer, while the user can optionally display other surface objects, such as the single 3D-reconstructed neuron (yellow). (b) 5D visualization of a series of multi-color 3D image stacks of <i>C. elegans</i> (courtesy of Rex Kerr). Different 3D viewing angles can be adjusted in real-time in Vaa3D, with which the user can freely change the displayed time point (bottom).</p

Examples of 3D microscopic images.

<p>(a) A confocal image of kinetochores (EGFP labeled) and chromosomes (histone-mCherry labeled) used in studying the first meiotic division in mouse oocytes <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Kitajima1" target="_blank">[17]</a>. (b) A confocal image of the first larval stage of <i>C. elegans </i><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Liu1" target="_blank">[18]</a>. Gray: DAPI labeled nuclei; yellow: myo3:EGFP. (c) A confocal image of an adult fruit fly brain <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Peng6" target="_blank">[19]</a>. Gray: NC82 labeled neuropil; green: ato-GAL4 (courtesy of Julie Simpson). (d) A serial section electron microscopic image of mouse visual cortex <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Bock1" target="_blank">[20]</a>. (e) A digital scanned laser light sheet fluorescence microscopic image of a Medaka juvenile <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002519#pcbi.1002519-Keller1" target="_blank">[21]</a>. Green: acetylated tubulin immuno-staining of the developing brain and spinal cord.</p

Often-used visualization methods for multi-dimensional microscopic image data.

<p>CB, color-blending; EM, electron microscopic images; FM, fluorescent microscopic images (often laser-scanning-microscopic images); HL, hardware-limited; WM, wide-field light microscopic images.</p

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis-3

<p><b>Copyright information:</b></p><p>Taken from "Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis"</p><p>http://www.biomedcentral.com/1471-2121/8/S1/S3</p><p>BMC Cell Biology 2007;8(Suppl 1):S3-S3.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1924508.</p><p></p> of thousands of individual nuclei. The human mammary epithelial cells were either non-neoplastic (top row) or malignant (bottom row) and were cultured in Matrigel™ (3D culture) for up to 12 days. Optical sections from 3D images, taken through the approximate midplane of individual nuclei are displayed. The optical sections were chosen to show representative features of the NuMA staining pattern. Panels a, b, c and d, show NuMA staining from non-neoplastic cells cultured for 3, 5, 10 and 12 days, representing cells present in incremental differentiation steps, respectively. Panels e, f, g, and h, show NuMA staining from malignant cells cultured for 4, 5, 10 and 11 days, representing cells present in tumors of increasing sizes, respectively. Notice that the nuclei of malignant cells are consistently larger than the nuclei of non-neoplastic cells. The bar represents 5 microns

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis-1

<p><b>Copyright information:</b></p><p>Taken from "Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis"</p><p>http://www.biomedcentral.com/1471-2121/8/S1/S3</p><p>BMC Cell Biology 2007;8(Suppl 1):S3-S3.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1924508.</p><p></p>eoplastic S1 cells. (b) The corresponding processed image section showing a composite view of the detected local bright features (light gray) of NuMA, extracted by the local bright feature analysis overlaid on the nuclear segmentation mask (dark gray). (c) Concentric terraces resulting from the application of the distance transform on the segmentation mask, which allows the radial distribution of NuMA to be calculated. (d) A set of LBF distribution profiles of NuMA calculated from differentiated non-neoplastic S1 cells. The relative density of NuMA bright features (ordinate) is plotted as a function of the relative distance from the perimeter (0.0) to the center (1.0) of the nuclei (abscissa)

Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis-2

<p><b>Copyright information:</b></p><p>Taken from "Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis"</p><p>http://www.biomedcentral.com/1471-2121/8/S1/S3</p><p>BMC Cell Biology 2007;8(Suppl 1):S3-S3.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1924508.</p><p></p>ys, 5 days, and 3 days respectively. There are 7 possible ways of grouping the phenotypes. Each row corresponds to one possible way. Different colors represent different phenotype groups. The first 3 rows correspond to grouping the 4 predefined phenotypes into 2 groups. The next 3 rows correspond to grouping the phenotypes into 3 groups, and the last row correspond to 4 groups. (b) Taking the 4 phenotype group case (last row in (a)) as an example, we used traditional clustering methods to divide the cluster histogram of the image (one cluster histogram per image) into the same number of clusters (i.e., 4 in this example). Each row corresponds to the clustering result of one method. (c) The -measures computed by pairing the phenotype group in the last row of (a) with each clustering result in (b). The maximum -score, which in this case is achieved by the Gaussian Mixture Model approach (GM), is selected as the of the corresponding cell phenotype grouping. (d) Confidence values as functions of different cases of phenotype groupings. We tested the confidence values under different number of clusters predefined for clustering LBF distributions using the five traditional methods (i.e., the second step of our algorithm, see Figure 6) as shown by dots of different colors. The numbers of clusters we tested were 4 to 26 with step size of 2. The consistent distribution of the dots indicates that our phenotype tree construction method is insensitive to the number of clusters we selected for clustering LBF distributions

For each gene at each phase, one representative embryo image is shown, followed by the manual annotations extracted from BDGP

<p><b>Copyright information:</b></p><p>Taken from "Automatic image analysis for gene expression patterns of fly embryos"</p><p>http://www.biomedcentral.com/1471-2121/8/S1/S7</p><p>BMC Cell Biology 2007;8(Suppl 1):S7-S7.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1924512.</p><p></p> A "◆" is used to mark the common annotations (see Appendix A for abbreviations.

Fly Light Split-GAL4 Driver Collection

<p>The data presented on this site are the work of the <a href="http://janelia.org/team-project/fly-light" target="_blank">Janelia FlyLight Project Team</a> and the laboratories of <a href="http://www.janelia.org/lab/rubin-lab" target="_blank">Gerald M. Rubin</a>. </p><p>The split-GAL4 lines can be requested from the Janelia fly facility by performing a search and adding the desired lines to your cart. You will then be able to use the FlyBank website to tell us where to send them. For additional help ordering lines, please contact us at <a href="mailto:flybank.janelia.org">flybank.janelia.org</a></p><p>In publications, please attribute the data presented on this site to one of the following papers, as follows: <br><br>For the overall strategy and methods used to produce the split-GAL4 lines for the mushroom body neurons: <br>Aso, Y., Hattori, D., Yu, Y., Johnston, R. M., Iyer, N., Ngo, T. B., Dionne, H., Abbott, L. F., Axel, R., Tanimoto, H. & Rubin, G. M. . The neuronal architecture of the mushroom body provides a logic for associative learning. <a href="http://elifesciences.org/content/3/e04577" target="_blank">eLife (2014) 3:e04577</a><br><br>For split-GAL4 lines for the Lobula Columnar (LC) visual projection neurons:<br>Wu, M., Nern, A., Williamson, W. R., Morimoto, M. M., Reiser, M. B., Card, G. M. & Rubin, G. M. Visual projection neurons in the Drosophila lobula link feature detection to distinct behavioral programs. under review<br><br>For refinement of the split-GAL4 vectors and methodology: <br>Pfeiffer, B. D., Ngo, T. T., Hibbard, K. L., Murphy, C., Jenett, A., Truman, J. W. & Rubin, G. M. Refinement of tools for targeted gene expression in Drosophila. <a href="http://www.genetics.org/content/186/2/735.long" target="_blank">Genetics (2010) 186: 735-55</a>. <br><br>For Multicolor Flp-out (MCFO) technique and single cell labeling:<br>Nern, A., Pfeiffer, B.D., and Rubin, G.M. Optimized tools for multicolor stochastic labeling reveal diverse stereotyped cell arrangements in the fly visual system. <a href="http://www.pnas.org/content/112/22/E2967.long" target="_blank">Proc Natl Acad Sci USA (2015) 112: E2967-2976</a>. <br><br>Split-GAL4 lines were designed based on the expression patterns of GAL4 driver lines in the adult nervous system: <br>The Janelia collection of lines is described in Jenett, A., Rubin, G.M., Ngo, T.-T. B., Shepherd, D., Murphy, C., Dionne, H., Pfeiffer, B.D., Cavallaro, A., Hall, D., Jeter, J., Iyer, N., Fetter, D., Hausenfluck, J.H., Peng, H., Trautman, E., Svirskas, R., Myers, G.W., Iwinski, Z.R., Aso, Y., DePasquale, G.M., Enos, A., Hulamm, P., Lam, S.C.B., Li, H-H., Laverty, T., Long, F., Qu, L., Murphy, S.D., Rokicki, K., Safford, T., Shaw, K., Simpson, J.H., Sowell, A., Tae, S., Yu, Y., Zugates, C.T. A GAL4-Driver Line Resource for Drosophila Neurobiology. <a href="http://www.cell.com/cell-reports/fulltext/S2211-1247(12)00292-6" target="_blank">Cell Reports (2012) 2: 991-1001</a> <br><br>The VT collection of lines is described in Kvon, E.Z., Kazmar, T., Stampfel, G., Yanez-Cuna, J.O., Pagani, M., Schernhuber, K., Dickson, B.J., and Stark, A. Genome-scale functional characterization of Drosophila developmental enhancers in vivo. <a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13395.html" target="_blank">Nature (2014) 512: 91-95</a> and Barry J. Dickson, unpublished data. <br><br>For opening and viewing h5j and LSM stacks:<br>Use <a href="http://fiji.sc/" target="_blank">Fiji</a> (<a href="http://fiji.sc/" target="_blank">http://fiji.sc</a>). Fiji has a built-in plugin (H5J_Loader_Plugin-1.0.4) for opening stack in h5j format, a "visually lossless" compression format.</p