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http://crcns.org

Website for brain experimental data and other resources such as stimuli and analysis tools. Provides marketplace and discussion forum for sharing tools and data in neuroscience. Data repository and collaborative tool that supports integration of theoretical and experimental neuroscience through collaborative research projects. CRCNS offers funding for new class of proposals focused on data sharing and other resources.

Proper citation: CRCNS (RRID:SCR_005608) Copy   

•   Source: SciCrunch Registry

http://www.oeb.harvard.edu/faculty/hartl/old_site/lab/publications/GeneMerge.html

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Web-based and standalone application that returns a wide range of functional genomic data for a given set of study genes and provides rank scores for over-representation of particular functions or categories in the data. It uses the hypergeometric test statistic which returns statistically correct results for samples of all sizes and is the #2 fastest GO tool available (Khatri and Draghici, 2005). GeneMerge can be used with any discrete, locus-based annotation data, including, literature references, genetic interactions, mutant phenotypes as well as traditional Gene Ontology queries. GeneMerge is particularly useful for the analysis of microarray data and other large biological datasets. The big advantage of GeneMerge over other similar programs is that you are not limited to analyzing your data from the perspective of a pre-packaged set of gene-association data. You can download or create gene-association files to analyze your data from an unlimited number of perspectives. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMerge (RRID:SCR_005744) Copy   

•   Source: SciCrunch Registry

https://www.synapse.org/

A cloud-based collaborative platform which co-locates data, code, and computing resources for analyzing genome-scale data and seamlessly integrates these services allowing scientists to share and analyze data together. Synapse consists of a web portal integrated with the R/Bioconductor statistical package and will be integrated with additional tools. The web portal is organized around the concept of a Project which is an environment where you can interact, share data, and analysis methods with a specific group of users or broadly across open collaborations. Projects provide an organizational structure to interact with data, code and analyses, and to track data provenance. A project can be created by anyone with a Synapse account and can be shared among all Synapse users or restricted to a specific team. Public data projects include the Synapse Commons Repository (SCR) (syn150935) and the metaGenomics project (syn275039). The SCR provides access to raw data and phenotypic information for publicly available genomic data sets, such as GEO and TCGA. The metaGenomics project provides standardized preprocessed data and precomputed analysis of the public SCR data.

Proper citation: Synapse (RRID:SCR_006307) Copy   

•   Source: SciCrunch Registry

http://neibank.nei.nih.gov

An integrated resource for genomics and bioinformatics in vision research including expressed sequence tag (EST) data and sequence-verified cDNA clones for multiple eye tissues of several species, web-based access to human eye-specific SAGE data through EyeSAGE, and comprehensive, annotated databases of known human eye disease genes and candidate disease gene loci. All expression- and disease-related data are integrated in EyeBrowse, an eye-centric genome browser. NEIBank provides a comprehensive overview of current knowledge of the transcriptional repertoires of eye tissues and their relation to pathology. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAST search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. To see the same region at the full UCSC site, cut and paste the location from the position window of the genome browser. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank.

Proper citation: NEIBank (RRID:SCR_007294) Copy   

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http://profiles.utsouthwestern.edu/profile/18453/franklin-hamra.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 18,2023. Stock center of Knockout and Transgenic Rats at UT Southwestern in Dallas.

Proper citation: Sperm Stem Cell Libraries for Biological Research (RRID:SCR_014189) Copy   

•   Source: SciCrunch Registry

http://actimetrics.com/products/clocklab/

Point and click program used to quickly analyse circadian activity data using algorithms and embedded controls to make every graph interactive and useful for data analysis. The analysis program has been used for a variety of species including mice, hamsters, rats, sheep, Drosophila, and humans. This program has three separate applications: one for data collection, one for analysis, and a chamber control program.

Proper citation: Clocklab (RRID:SCR_014309) Copy   

•   Source: SciCrunch Registry

http://www.callisto-science.org/NSI/Neuroscience_Image_Database/Rat_Brain_Atlas.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 27,2025. Compact 3rd edition of The Rat Brain Atlas of Paxinos & Watson published in 1997, it is the most widely used stereotaxic reference system for rat brain. The illustrations and nomenclature of the atlas have become standard tools used by almost all research neuroscientists who deal with anatomy, physiology, or function. It has been subsequently updated, with the 6th edition being the most recent. The 3rd edition is the most recent one available online for free. The program runs in Adobe Acrobat Reader.

Proper citation: Rat Brain Atlas of Paxinos and Watson (RRID:SCR_006369) Copy   

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http://www.nitrc.org/projects/dti_rat_atlas/

3D DTI anatomical rat brain atlases have been created by the UNC- Chapel Hill Department of Psychiatry and the CAMID research collaboration. There are three age groups, postnatal day 5, postnatal day 14, and postnatal day 72. The subjects were Sprague-Dawley rats that were controls in a study on cocaine abuse and development. The P5 and P14 templates were made from scans of twenty rats each (ten female, ten male); the P72, from six females. The individual cases have been resampled to isotropic resolution, manually skull-stripped, and deformably registered via an unbiased atlas building method to create a template for each age group. Each template was then manually segmented using itk-SNAP software. Each atlas is made up of 3 files, a template image, a segmentation, and a label file.

Proper citation: 3D DTI Atlas of the Rat Brain In Postnatal Day 5 14 and Adulthood (RRID:SCR_009437) Copy   

•   Source: SciCrunch Registry

http://mirdb.org/miRDB/

An online database for miRNA target prediction and functional annotations.

Proper citation: miRDB (RRID:SCR_010848) Copy   

•   Source: SciCrunch Registry

http://targetscan.org/

Web tool to predict biological targets of miRNAs by searching for presence of conserved 8mer, 7mer and 6mer sites that match seed region of each miRNA. Nonconserved sites are also predicted and sites with mismatches in seed region that are compensated by conserved 3' pairing. Used to search for predicted microRNA targets in mammals.

Proper citation: TargetScan (RRID:SCR_010845) Copy   

•   Source: SciCrunch Registry

http://adacgh.bioinfo.cnio.es/

A web tool for the analysis of aCGH data sets. They focus on calling gains and losses and estimating the number of copy changes. Note: ADaCGH will continue being maintained, but is deprecated. Their new tool for CGH and CNV is WaviCGH, http://wavi.bioinfo.cnio.es/

Proper citation: ADaCGH (RRID:SCR_010916) Copy   

•   Source: SciCrunch Registry

https://github.com/scimemia/M-Track

Source code that allows users to simultaneously track the movement of individual paws during spontaneous grooming episodes and walking in multiple freely-behaving mice/rats. This toolbox provides a simple platform to perform trajectory analysis of paw movement.

Proper citation: M-Track (RRID:SCR_015865) Copy   

•   Source: SciCrunch Registry

http://www.microrna.org

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: microRNA.org (RRID:SCR_006997) Copy   

•   Source: SciCrunch Registry

http://brainmaps.org

An interactive multiresolution brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and integrated with a high-speed database for querying and retrieving data about brain structure and function. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, Tyto alba and many other vertebrates. BrainMaps is currently accepting histochemical, immunocytochemical, and tracer connectivity data, preferably whole-brain. In addition, they are interested in EM, MRI, and DTI data.

Proper citation: BrainMaps.org (RRID:SCR_006878) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

https://github.com/Sethupathy-Lab/miRquant

Software tool for accurate annotation and quantification of microRNAs and their isomiRs from small RNA-sequencing data. Provides information on quality of sequencing data, genome mapping statistics, abundance of other types of small RNAs such as tDRs and yDRs, prevalence of post transcriptional modifications.

Proper citation: miRquant (RRID:SCR_017261) 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://ctdbase.org/

A public database that enhances understanding of the effects of environmental chemicals on human health. Integrated GO data and a GO browser add functionality to CTD by allowing users to understand biological functions, processes and cellular locations that are the targets of chemical exposures. CTD includes curated data describing cross-species chemical–gene/protein interactions, chemical–disease and gene–disease associations to illuminate molecular mechanisms underlying variable susceptibility and environmentally influenced diseases. These data will also provide insights into complex chemical–gene and protein interaction networks.

Proper citation: Comparative Toxicogenomics Database (CTD) (RRID:SCR_006530) Copy   

•   Source: SciCrunch Registry