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http://krasnow1.gmu.edu/cn3/hippocampus3d/

Data files for a high resolution three dimensional (3D) structure of the rat hippocampus reconstructed from histological sections. The data files (supplementary data for Ropireddy et al., Neurosci., 2012 Mar 15;205:91-111) are being shared on the Windows Live cloud space provided by Microsoft. Downloadable data files include the Nissl histological images, the hippocampus layer tracings that can be visualized alone or superimposed to the corresponding Nissl images, the voxel database coordinates, and the surface rendering VRML files. * Hippocampus Nissl Images: The high resolution histological Nissl images obtained at 16 micrometer inter-slice distance for the Long-Evans rat hippocampus can be downloaded or directly viewed in a browser. This dataset consists of 230 jpeg images that cover the hippocampus from rostral to caudal poles. This image dataset is uploaded in seven parts as rar files. * Hippocampus Layer Tracings: The seven hippocampus layers ''ML, ''GC'', ''HILUS'' in DG and ''LM'', ''RAD'', ''PC'', ''OR'' in CA were segmented (traced) using the Reconstruct tool which can be downloaded from Synapse web. This tool outputs all the tracings for each image in XML format. The XML tracing files for all these seven layers for each of the above Nissl images are zipped into one file and can be downloaded. * Hippocampus VoxelDB: The 3D hippocampus reconstructed is volumetrically transformed into 16 micrometer sized voxels for all the seven layers. Each voxel is reported according to multiple coordinate systems, namely in Cartesian, along the natural hippocampal dimensions, and in reference to the canonical brain planes. The voxel database file is created in ascii format. The single voxel database file was split into three rar archive files. Please note that the three rar archive files should be downloaded and decompressed in a single directory in order to obtain the single voxel data file (Hippocampus-VoxelDB.txt). * 3D Surface Renderings: This is a rar archive file with a single VRML file containing the surface rendering of DG and CA layers. This VRML file can be opened and visualized in any VRML viewer, e.g. the open source software view3dscene. * 3D Hippocampus Movie: This movie contains visualization of the 3D surface renderings of CA (blue) and DG (red) inner and outer boundaries; neuronal embeddings of DG granule and CA pyramidal dendritic arbors; potential synapses between CA3b interneuron axon and pyramidal dendrite, and between CA2 pyramidal axon and CA pyramidal dendrites.

Proper citation: Hippocampus 3D Model (RRID:SCR_005083) Copy   

•   Source: SciCrunch Registry

http://genenet2.uthsc.edu/geneinfoviz/search.php

GeneInfoViz is a web based tool for batch retrieval of gene function information, visualization of GO structure and construction of gene relation networks. It takes a input list of genes in the form of LocusLink ID, UniGeneID, gene symbol, or accession number and returns their functional genomic information. Based on the GO annotations of the given genes, GeneInfoViz allows users to visualize these genes in the DAG structure of GO, and construct a gene relation network at a selected level of the DAG. Platform: Online tool

Proper citation: GeneInfoViz (RRID:SCR_005680) Copy   

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http://neuroviisas.med.uni-rostock.de/neuroviisas.html

An open framework for integrative data analysis, visualization and population simulations for the exploration of network dynamics on multiple levels. This generic platform allows the integration of neuroontologies, mapping functions for brain atlas development, and connectivity data administration; all of which are required for the analysis of structurally and neurobiologically realistic simulations of networks. What makes neuroVIISAS unique is the ability to integrate neuroontologies, image stacks, mappings, visualizations, analyzes and simulations to use them for modelling and simulations. Based on the analysis of over 2020 tracing studies, atlas terminologies and registered histological stacks of images, neuroVIISAS permits the definition of neurobiologically realistic networks that are transferred to the simulation engine NEST. The analysis on a local and global level, the visualization of connectivity data and the results of simulations offer new possibilities to study structural and functional relationships of neural networks. neuroVIISAS provide answers to questions like: # How can we assemble data of tracing studies? (Metastudy) # Is it possible to integrate tracing and brainmapping data? (Data Integration) # How does the network of analyzed tracing studies looks like? (Visualization) # Which graph theoretical properties posses such a network? (Analysis) # Can we perform population simulations of a tracing study based network? (Simulation and higher level data integration) neuroVIISAS can be used to organize mapping and connectivity data of central nervous systems of any species. The rat brain project of neuroVIISAS contains 450237 ipsi- and 175654 contralateral connections. A list of evaluated tracing studies are available. PyNEST script generation does work using WINDOWS OS, however, the script must be transferred to a UNIX OS with installed NEST. The results file of the NEST simulation can be visualized and analyzed by neuroVIISAS on a WINDOWS OS.

Proper citation: neuroVIISAS (RRID:SCR_006010) Copy   

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http://phenomebrowser.net/

PhenomeNet is a cross-species phenotype similarity network. It contains the experimentally observed phenotypes of multiple species as well as the phenotypes of human diseases. PhenomeNet provides a measure of phenotypic similarity between the phenotypes it contains. The latest release (from 22 June 2012) contains 124,730 complex phenotype nodes taken from the yeast, fish, worm, fly, rat, slime mold and mouse model organism databases as well as human disease phenotypes from OMIM and OrphaNet. The network is a complete graph in which edge weights represent the degree of phenotypic similarity. Phenotypic similarity can be used to identify and prioritize candidate disease genes, find genes participating in the same pathway and orthologous genes between species. To compute phenotypic similarity between two sets of phenotypes, we use a weighted Jaccard index. First, phenotype ontologies are used to infer all the implications of a phenotype observation using several phenotype ontologies. As a second step, the information content of each phenotype is computed and used as a weight in the Jaccard index. Phenotypic similarity is useful in several ways. Phenotypic similarity between a phenotype resulting from a genetic mutation and a disease can be used to suggest candidate genes for a disease. Phenotypic similarity can also identify genes in a same pathway or orthologous genes. PhenomeNet uses the axioms in multiple species-dependent phenotype ontologies to infer equivalent and related phenotypes across species. For this purpose, phenotype ontologies and phenotype annotations are integrated in a single ontology, and automated reasoning is used to infer equivalences. Specifically, for every phenotype, PhenomeNet infers the related mammalian phenotype and uses the Mammalian Phenotype Ontology for computing phenotypic similarity. Tools: * PhenomeBLAST - A tool for cross-species alignments of phenotypes * PhenomeDrug - method for drug-repurposing

Proper citation: phenomeNET (RRID:SCR_006165) Copy   

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http://bluebrain.epfl.ch/

A Swiss-led project with the aim of reverse engineering the mammalian brain and achieving a complete virtual human brain. The researchers have demonstrated the validity of their method by developing a realistic model of a rat cortical column, consisting of about 10,000 neurons. The eventual goal is to simulate systems of millions and hundreds of millions of neurons. The virtual brain will be an exceptional tool giving neuroscientists a new understanding of the brain and a better understanding of neurological diseases. In five years of work, Henry Markram's team has perfected a facility that can create realistic models of one of the brain's essential building blocks. This process is entirely data driven and essentially automatically executed on the supercomputer. Meanwhile the generated models show a behavior already observed in years of neuroscientific experiments. These models will be basic building blocks for larger scale models leading towards a complete virtual brain.

Proper citation: Blue Brain Project (RRID:SCR_002994) Copy   

•   Source: SciCrunch Registry

http://brainarray.mbni.med.umich.edu/Brainarray/Database/ProbeMatchDB/ncbi_probmatch_para_step1.asp

Matches a list of microarray probes across different microrarray platforms (GeneChip, EST from different vendors, Operon Oligos) and species (human, mouse and rat), based on NCBI UniGene and HomoloGene. The capability to match protein sequence IDs has just been added to facilitate proteomic studies. The ProbeMatchDB is mainly used for the design of verification experiments or comparing the microarray results from different platforms. It can be used for finding equivalent EST clones in the Research Genetics sequence verified clone set based on results from Affymetirx GeneChips. It will also help to identify probes representing orthologous genes across human, mouse and rat on different microarray platforms.

Proper citation: ProbeMatchDB 2.0 (RRID:SCR_003433) Copy   

•   Source: SciCrunch Registry

http://ucsfeye.net/mlavailRDratmodels.shtml

Supplier of fully penetrant rat models of the retinitis pigmentosa type of inherited retinal degeneration, including the following models: * Mutant rhodopsin transgenic rats ** P23H mutant rhodopsin transgenic rats -Three lines with different rates of photoreceptor degeneration ** S334ter mutant rhodopsin transgenic rats -Five lines with different rates of photoreceptor degeneration * RCS (Royal College of Surgeons) rats with inherited retinal dystrophy ** RCS pink-eyed inbred strain ** RCS pigmented congenic strain with slowed rate of retinal dystrophy ** RCS congenic control strains of both pigmentation types, wild-type at the retinal dystrophy (Mertk) genetic locus The resource has been supported by the National Eye Institute (NEI) for the past 19 years to produce and distribute breeding pairs of these animal models to vision scientists. Thus, the following apply: * Request for rats requires only a 1-page letter/e-mail addressing 4 questions * No charge for the animals or tissues (except for shipping costs) * No Material Transfer Agreement (MTA) required * No collaboration requirement (in most cases) The resource usually provides multiple breeding pairs of the rats to vision scientists to generate breeding stock. It can also provide extra animals to breed for immediate experimental work, animals of specific ages (depending upon availability), animals with prior exposure to different lighting conditions, eyes taken at specific ages instead of rats for pilot studies and other experiments (fresh, frozen, dissected in specific ways, or fixed with special fixatives or by different methods), or other tissues (e.g., liver, spleen, brain, testis, etc.) prepared different ways.

Proper citation: Retinal Degeneration Rat Model Resource (RRID:SCR_003311) Copy   

•   Source: SciCrunch Registry

http://spine.rutgers.edu/microarray/

Database which provides on-line searching of microarray datasets generated from rat spinal cord after contusion injury. Both the primary injury site and a site 5 mm distal to the injury site were assayed. Tissue was obtained from Long Evans rats subject to spinal cord contusion injury using the MASCIS impactor (formerly known as the NYU impactor). RNA expression was assayed at the site of injury and distal to the site of injury using the Affymetrix Rat Neuro U34 chip.

Proper citation: Gene Expression Profiling in Spinal Cord Injury (RRID:SCR_003260) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/embryonic-stem-cell-core

The Murine Embryonic Stem Cell Core has been created to help you create mutations in murine embryonic stem cells. The core has several missions including development of state-of-the-art reagents for the production of targeted mutations in embryonic stem cells, the creation of quality-controlled embryonic stem cell lines, and the teaching of methods for embryonic stem cell culture and manipulation. The core utilizes quality-controlled cells developed here at Washington University.

Proper citation: WUSTL School of Medicine Embryonic Stem Cell Core (RRID:SCR_012441) Copy   

•   Source: SciCrunch Registry

http://www.einstein.yu.edu/centers/liver-research/research-cores/special-animals-core.aspx

Core that provides resources, technologies and scientific expertise to advance translational applications of animal and human liver cells. It also provides bred animals for research, isolation and culture of animal and human liver cells, as well as provision of cell culture additives and materials.

Proper citation: Marion Bessin Liver Research Center Animal Models Stem Cells and Cell Therapy (RRID:SCR_015181) Copy   

•   Source: SciCrunch Registry

http://derc.yale.edu/cores/physiology.aspx

Fee-for-service core facility for DRC members to facilitate in vivo diabetes-related research dealing with biological outcomes in normal, diabetic, and genetically manipulated rodents and mice. Physiology Core is divided into two Sub-cores: the Animal Surgery and Experimental Procedure Sub-core, which provides assistance with in vivo rodent studies the Analytical Sub-core, which assists with measurement of various analytes in rat and mouse samples.

Proper citation: Yale Diabetes Research Center Physiology Core Facility (RRID:SCR_015147) Copy   

•   Source: SciCrunch Registry