Tools   Select Another Resource Report Type

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

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http://polya.umdnj.edu/

A database of mRNA polyadenylation sites. PolyA_DB version 1 contains human and mouse poly(A) sites that are mapped by cDNA/EST sequences. PolyA_DB version 2 contains poly(A) sites in human, mouse, rat, chicken and zebrafish that are mapped by cDNA/EST and Trace sequences. Sequence alignments between orthologous sites are available. PolyA_SVM predicts poly(A) sites using 15 cis elements identified for human poly(A) sites.

Proper citation: PolyA DB (RRID:SCR_007867) Copy   

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http://wukong.tongji.edu.cn/pepid

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A database to store the curated epigenetic data from studies of prostate cancer retrieved by literature mining. The Prostate Epigenetic Database (PEpiD) is meant as a resource for finding previous studies of prostate cancer in humans, mice and rats. Searches can be targeted through the categories of DNA methylation, histone modification, and microRNA.

Proper citation: PEpiD (RRID:SCR_000235) Copy   

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https://bams1.org/connectomes/standard_rat.php, https://bams1.org/connectomes/custom_rat.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9,2022. Database of information about brain region circuitry, it collates data from the literature on tract tracing studies and provides tools for analysis and visualization of connectivity between brain regions., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BAMS Connectivity (RRID:SCR_000561) Copy   

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http://lifespandb.sageweb.org/

Database that collects published lifespan data across multiple species. The entire database is available for download in various formats including XML, YAML and CSV.

Proper citation: Lifespan Observations Database (RRID:SCR_001609) Copy   

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http://mint.bio.uniroma2.it/

A database that focuses on experimentally verified protein-protein interactions mined from the scientific literature by expert curators. The curated data can be analyzed in the context of the high throughput data and viewed graphically with the MINT Viewer. This collection of molecular interaction databases can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. VirusMINT explores the interactions of viral proteins with human proteins. The MINT connect viewer allows you to enter a list of proteins (e.g. proteins in a pathway) to retrieve, display and download a network with all the interactions connecting them.

Proper citation: MINT (RRID:SCR_001523) Copy   

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http://proteomics.ucsd.edu/Software/NeuroPedia/index.html

A neuropeptide encyclopedia of peptide sequences (including genomic and taxonomic information) and spectral libraries of identified MS/MS spectra of homolog neuropeptides from multiple species.

Proper citation: NeuroPedia (RRID:SCR_001551) Copy   

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http://fairbrother.biomed.brown.edu/spliceman/index.cgi

An online tool that takes a set of DNA sequences with point mutations and returns a ranked list to predict the effects of point mutations on pre-mRNA splicing. The current implementation includes 11 genomes: human, chimp, rhesus, mouse, rat, dog, cat, chicken, guinea pig, frog and zebrafish.

Proper citation: Spliceman (RRID:SCR_005354) Copy   

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http://edwardslab.bmcb.georgetown.edu/downloads/

The Peptide Sequence Database contains putative peptide sequences from human, mouse, rat, and zebrafish. Compressed to eliminate redundancy, these are about 40 fold smaller than a brute force enumeration. Current and old releases are available for download. Each species'' peptide sequence database comprises peptide sequence data from releveant species specific UniGene and IPI clusters, plus all sequences from their consituent EST, mRNA and protein sequence databases, namely RefSeq proteins and mRNAs, UniProt''s SwissProt and TrEMBL, GenBank mRNA, ESTs, and high-throughput cDNAs, HInv-DB, VEGA, EMBL, IPI protein sequences, plus the enumeration of all combinations of UniProt sequence variants, Met loss PTM, and signal peptide cleavages. The README file contains some information about the non amino-acid symbols O (digest site corresponding to a protein N- or C-terminus) and J (no digest sequence join) used in these peptide sequence databases and information about how to configure various search engines to use them. Some search engines handle (very) long sequences badly and in some cases must be patched to use these peptide sequence databases. All search engines supported by the PepArML meta-search engine can (or can be patched to) successfully search these peptide sequence databases.

Proper citation: Peptide Sequence Database (RRID:SCR_005764) Copy   

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http://www.disgenet.org

Database and discovery platform containing publicly available collections of genes and variants associated to human diseases. Integrates data from curated repositories, GWAS catalogues, animal models and scientific literature.

Proper citation: DisGeNET (RRID:SCR_006178) Copy   

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http://genetrail.bioinf.uni-sb.de/

A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneTrail (RRID:SCR_006250) Copy   

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http://www.civm.duhs.duke.edu/neuro2012ratatlas/

Multidimensional atlas of the adult Wistar rat brain based on magnetic resonance histology (MRH). The atlas has been carefully aligned with the widely used Paxinos-Watson atlas based on optical sections to allow comparisons between histochemical and immuno-marker data, and the use of the Paxinos-Watson abbreviation set. Our MR atlas attempts to make a seamless connection with the advantageous features of the Paxinos-Watson atlas, and to extend the utility of the data through the unique capabilities of MR histology: a) ability to view the brain in the skull with limited distortion from shrinkage or sectioning; b) isotropic spatial resolution, which permits sectioning along any arbitrary axis without loss of detail; c) three-dimensional (3D) images preserving spatial relationships; and d) widely varied contrast dependent on the unique properties of water protons. 3D diffusion tensor images (DTI) at what we believe to be the highest resolution ever attained in the rat provide unique insight into white matter structures and connectivity. The 3D isotropic data allow registration of multiple data sets into a common reference space to provide average atlases not possible with conventional histology. The resulting multidimensional atlas that combines Paxinos-Watson with multidimensional MRH images from multiple specimens provides a new, comprehensive view of the neuroanatomy of the rat and offers a collaborative platform for future rat brain studies. To access the atlas, click view supplementary materials in CIVMSpace at the bottom of the following webpage.

Proper citation: Adult Wistar Rat Atlas (RRID:SCR_006288) Copy   

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https://www.signalingpathways.org/ominer/query.jsf

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on February 25, 2022.Software tool as knowledge environment resource that accrues, develops, and communicates information that advances understanding of structure, function, and role in disease of nuclear receptors (NRs) and coregulators. It specifically seeks to elucidate roles played by NRs and coregulators in metabolism and development of metabolic disorders. Includes large validated data sets, access to reagents, new findings, library of annotated prior publications in field, and journal covering reviews and techniques.As of March 20, 2020, NURSA is succeeded by the Signaling Pathways Project (SPP).

Proper citation: Nuclear Receptor Signaling Atlas (RRID:SCR_003287) Copy   

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http://www.chibi.ubc.ca/Gemma

Resource for reuse, sharing and meta-analysis of expression profiling data. Database and set of tools for meta analysis, reuse and sharing of genomics data. Targeted at analysis of gene expression profiles. Users can search, access and visualize coexpression and differential expression results.

Proper citation: Gemma (RRID:SCR_008007) Copy   

•   Source: SciCrunch Registry

http://www.brainnav.com

THIS RESOURCE IS NO LONGER IN SERVICE, documented December 31, 2013. An interactive atlas and 3D brain software for research, structure analysis, and education, it offers six atlases representing four species: the mouse, rat, monkey and human. The stereotaxic coordinates atlases are available for all four species and the rodent models have additional chemoarchitectonic atlases. BrainNavigator helps locate specific areas of the brain, making visualizing and experimental planning in the brain easier. *Plan: Browse 6 Atlases, Visualize with 3D models, Search Literature, Analyze gene expression, Identify connections *Publish: Access reference tools, Use and print images for publication, Search literature *Propose: Use and print images for proposals, Search literature, Locate gene expression in 2D and 3D, Identify connections *Produce: Simulate injections, Customize new coordinates, virtually slice sections, overlay atlas maps on your own images, create personal atlas maps With BrainNavigator, you''ll gain 24/7 access to their powerful 3D brain interactive software tool that helps further research in the neurosciences. In addition, their vast library of widely respected and referenced brain publications will provide a plethora of information on the most current brain research available. As publisher of the gold standard in brain atlas publications authored by the team around the leading brain cartographers George Paxinos and Charles Watson, they are pleased to bring an advanced tool to today''s neuroscientists and educators. Combining atlas content and 3D capabilities based on technologies from the Allen Institute for Brain Science, this online workflow solution brings brain research, analysis and education tools to your fingertips.

Proper citation: BrainNavigator (RRID:SCR_008289) Copy   

•   Source: SciCrunch Registry

http://appris.bioinfo.cnio.es/

A database that houses annotations of human splice isoforms. It adds reliable protein structural and functional data and information from cross-species conservation. A visual representation of the annotations for each gene allows users to easily identify functional changes brought about by splicing events. In addition to collecting, integrating and analyzing reliable predictions of the effect of splicing events, it also selects a single reference sequence for each gene, termed the principal isoform, based on the annotations of structure, function and conservation for each transcript.

Proper citation: APPRIS (RRID:SCR_012019) Copy   

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http://compartments.jensenlab.org/Downloads

Web resource that integrates evidence on protein subcellular localization from manually curated literature, high-throughput screens, automatic text mining, and sequence-based prediction methods. All evidence is mapped to common protein identifiers and Gene Ontology terms, and further unify it by assigning confidence scores that facilitate comparison of the different types and sources of evidence and visualize these scores on a schematic cell.

Proper citation: COMPARTMENTS Subcellular localization database (RRID:SCR_015561) Copy   

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https://www.tfcheckpoint.org/

Collection of transcription factors annotated according to experimental and other evidence on their function as true DbTFs. Provides reference for both small scale experiments and genome scale studies. Curated compendium of specific DNA-binding RNA polymerase II transcription factors.

Proper citation: tfcheckpoint (RRID:SCR_023880) 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   

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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   

•   Source: SciCrunch Registry