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http://ccdb.ucsd.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented June 5, 2017. It has been merged with Cell Image Library. Database for sharing and mining cellular and subcellular high resolution 2D, 3D and 4D data from light and electron microscopy, including correlated imaging that makes unique and valuable datasets available to the scientific community for visualization, reuse and reanalysis. Techniques range from wide field mosaics taken with multiphoton microscopy to 3D reconstructions of cellular ultrastructure using electron tomography. Contributions from the community are welcome. The CCDB was designed around the process of reconstruction from 2D micrographs, capturing key steps in the process from experiment to analysis. The CCDB refers to the set of images taken from microscope the as the Microscopy Product. The microscopy product refers to a set of related 2D images taken by light (epifluorescence, transmitted light, confocal or multiphoton) or electron microscopy (conventional or high voltage transmission electron microscopy). These image sets may comprise a tilt series, optical section series, through focus series, serial sections, mosaics, time series or a set of survey sections taken in a single microscopy session that are not related in any systematic way. A given set of data may be more than one product, for example, it is possible for a set of images to be both a mosaic and a tilt series. The Microscopy Product ID serves as the accession number for the CCDB. All microscopy products must belong to a project and be stored along with key specimen preparation details. Each project receives a unique Project ID that groups together related microscopy products. Many of the datasets come from published literature, but publication is not a prerequisite for inclusion in the CCDB. Any datasets that are of high quality and interest to the scientific community can be included in the CCDB.

Proper citation: Cell Centered Database (RRID:SCR_002168) Copy   

•   Source: SciCrunch Registry

https://www.genevestigator.com/gv/

A high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.

Proper citation: Genevestigator (RRID:SCR_002358) Copy   

•   Source: SciCrunch Registry

http://www.theearlab.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13, 2026. Computationally oriented experimental laboratory interested in the encoding of auditory information in the cerebral cortex and brainstem, and in the mechanisms of tinnitus and the effect of various drugs (Lidocaine, steroids, anti-oxidants) in relieving noise trauma induced tinnitus. The ferret (Mustela putorius) and the rat serve as their system model. Through chronic implants, they obtain electrophysiological data from awake behaving animals in order to investigate the response properties and functional organization of the auditory system, both in health and after noise trauma that induces tinnitus in rats. Projects: * Response Modulation to Ongoing Broadband Sounds in Primary Auditory Cortex * Neuronal Response Characteristics in the Inferior Colliculus of the Awake Ferret and Rat * Spectro-Temporal Representation of Feature Onsets in Primary Auditory Cortex * Targeting the changes in inferior colliculus induced by tinnitus

Proper citation: Ear Lab (RRID:SCR_002531) Copy   

•   Source: SciCrunch Registry

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://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   

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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://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://synapses.clm.utexas.edu

A portal into the 3D ultrastructure of the brain providing: Anatomy of astrocytes, axons, dendrites, hippocampus, organelles, synapses; procedures of 3D reconstruction and tissue preparation; as well as an atlas of ultrastructural neurocytology (by Josef Spacek), online aligned images, and reconstructed dendrites. Synapse Web hosts an ultrastructural atlas containing more than 500 electron micrographs (added to regularly) that identify unique ultrastructural and cellular components throughout the brain. Additionally, Synapse Web has raw images, reconstructions, and quantitative data along with tutorial instructions and numerous tools for investigating the functional structure of objects that have been serial thin sectioned for electron microscopy.

Proper citation: Synapse Web (RRID:SCR_003577) Copy   

•   Source: SciCrunch Registry

http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM294644.pdf

Serum / plasma biomarkers, Cardiac troponins T (cTnT) and I (cTnI), in safety assessment studies for rats, dogs, and monkeys are qualified biomarkers for the following contexts of use: # When there is previous indication of cardiac structural damage with a particular drug, cardiac troponin testing can help estimate a lowest toxic dose or a highest non-toxic dose to help choose doses for human testing. In this case, cardiac troponins may serve as a clinical chemistry correlate to the histology. For example, in a safety assessment study, lower doses without increases in cardiac troponins may be used to support a no observed effect level (NOEL) identified by histology. # When there is known cardiac structural damage with a particular pharmacologic class of a drug and histopathologic analyses do not reveal structural damage, circulating cardiac troponins may be used to support or refute the inference of low cardiotoxic potential. # When unexpected cardiac structural toxicity is found in a nonclinical study, the retroactive (reflex) examination of serum or plasma from that study for cardiac troponins can be used to help determine a no observed adverse effect level (NOAEL) or lowest observed adverse effect level (LOAEL). The results of this testing may support inclusion of cardiac troponin testing in subsequent safety assessment studies.

Proper citation: O'Brien Reagan York and Jacobsen Drug-induced Cardiotoxicity Biomarkers (RRID:SCR_003717) Copy   

•   Source: SciCrunch Registry

http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DrugDevelopmentToolsQualificationProgram/UCM285010.pdf

Urinary kidney biomarkers, Clusterin and Renal Papillary Antigen-1 (RPA-1), that sponsors may use to determine more conservative NOAELs for estimating starting doses in the initial human clinical trial of a drug that displays nonclinical nephrotoxicity as determined by histopathology. When tested with a limited number of nephrotoxic compounds, the Receiver Operating Characteristic (ROC) analyses showed that urinary clusterin and renal papillary antigen-1 (RPA-1) have better sensitivity and specificity than BUN and creatinine for the detection of specific kidney pathologies in male rats. Clusterin and RPA-1 provide additional and complementary information to BUN, serum creatinine (sCr), and histopathology for the detection of acute drug-induced nephrotoxicity in safety assessment studies.

Proper citation: ILSI HESI Drug-induced Nephrotoxicity Biomarkers (RRID:SCR_003716) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) 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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www-personal.umich.edu/~brdsmith/Research.html

Data set of image collections and movies including Magnetic Resonance Imaging of Embryos, Human Embryo Imaging, MRI of Cardiovascular Development, and Live Embryo Imaging. Individual MRI slice images, three-dimensional images, animations, stereo-pair animations, animations of organ systems, and photo-micrographs are included.

Proper citation: Brad Smith Magnetic Resonance Imaging of Embryos (RRID:SCR_006300) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

•   Source: SciCrunch Registry

http://brainvis.wustl.edu/wiki/index.php/Caret:Atlases

THIS RESOURCE IS NO LONGER IS SERVICE. Documented on July,29,2022. Surface-based atlases of human, macaque, rat and mouse cerebral and cerebellar cortices derived from structural MRI volumes developed in the Van Essen laboratory can be downloaded by direct links on the SumsDB database and can be viewed using freely available Caret (offline) and WebCaret (online) software. The human and macaque atlases include a large and growing compendium of experimental data pertaining to the structural and functional organization of primate cerebral cortex.

Proper citation: Surface-Based Atlases (RRID:SCR_002099) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/funcassociate/

A web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 37 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff. A new version of FuncAssociate supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented. Platform: Online tool

Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) Copy   

•   Source: SciCrunch Registry

http://www.btool.org/ADGO2

A web-based tool that provides composite interpretations for microarray data comparing two sample groups as well as lists of genes from diverse sources of biological information. It provides multiple gene set analysis methods for microarray inputs as well as enrichment analyses for lists of genes. It screens redundant composite annotations when generating and prioritizing them. It also incorporates union and subtracted sets as well as intersection sets. Users can upload their gene sets (e.g. predicted miRNA targets) to generate and analyze new composite sets.

Proper citation: ADGO (RRID:SCR_006343) Copy   

•   Source: SciCrunch Registry

http://wavi.bioinfo.cnio.es/

A versatile web-server application for the analysis and visualization of array-CGH data.

Proper citation: waviCGH (RRID:SCR_006662) Copy   

•   Source: SciCrunch Registry