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http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

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http://www.jax.org/cyto/index.html

Maintains and distributes chromosome aberration stocks that provide primarily mouse models for Down syndrome. The Resource currently provides models for Down syndrome research, including: Rb(6.16)24Lub x Rb(16.17)7Bnr F1 hybrids that are used to produce Chr 16 trisomy (Ts16) embryos, which have many of the fetal developmental features of DS, and; Ts(1716)65Dn, segmental trisomy mice that survive to adulthood and have many of the features of DS. The Resource also includes stocks with selected reciprocal translocations involving Chr 16 and some Chr 16 transgenic stocks. In addition, a large number of Robertsonian chromosome stocks are held as frozen embryos in the Cryopreservation Resource. Each mouse chromosome is present in at least two different Robertsonian chromosomes in these strains so that specific trisomies for each of the 19 mouse autosomes can be produced. Breeding pairs and individual mice are provided.

Proper citation: Jackson Laboratory Cytogenetic Models Resource (RRID:SCR_003270) Copy   

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http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

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http://phenome.jax.org/

Database enables integration of genomic and phenomic data by providing access to primary experimental data, data collection protocols and analysis tools. Data represent behavioral, morphological and physiological disease-related characteristics in naive mice and those exposed to drugs, environmental agents or other treatments. Collaborative standardized collection of measured data on laboratory mouse strains to characterize them in order to facilitate translational discoveries and to assist in selection of strains for experimental studies. Includes baseline phenotype data sets as well as studies of drug, diet, disease and aging effect., protocols, projects and publications, and SNP, variation and gene expression studies. Provides tools for online analysis. Data sets are voluntarily contributed by researchers from variety of institutions and settings, or retrieved by MPD staff from open public sources. MPD has three major types of strain-centric data sets: phenotype strain surveys, SNP and variation data, and gene expression strain surveys. MPD collects data on classical inbred strains as well as any fixed-genotype strains and derivatives that are openly acquirable by the research community. New panels include Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. Phenotype data include measurements of behavior, hematology, bone mineral density, cholesterol levels, endocrine function, aging processes, addiction, neurosensory functions, and other biomedically relevant areas. Genotype data are primarily in the form of single-nucleotide polymorphisms (SNPs). MPD curates data into a common framework by standardizing mouse strain nomenclature, standardizing units (SI where feasible), evaluating data (completeness, statistical power, quality), categorizing phenotype data and linking to ontologies, conforming to internal style guides for titles, tags, and descriptions, and creating comprehensive protocol documentation including environmental parameters of the test animals. These elements are critical for experimental reproducibility.

Proper citation: Mouse Phenome Database (MPD) (RRID:SCR_003212) Copy   

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http://mouseNET.princeton.edu

A functional network for laboratory mouse based on integration of diverse genetic and genomic data. It allows the users to accurately predict novel functional assignments and network components. MouseNET uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the mouseNET algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. The graph may be explored further. As you move the mouse over genes in the network, interactions involving these genes are highlighted.If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed.

Proper citation: MouseNET (RRID:SCR_003357) Copy   

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http://www.reactome.org

Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.

Proper citation: Reactome (RRID:SCR_003485) Copy   

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http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

•   Source: SciCrunch Registry

http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

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http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

•   Source: SciCrunch Registry

http://brainstars.org

BrainStars (or B*) is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions. For 51 CNS regions, slices (0.5-mm thick) of mouse brain were cut on a Mouse Brain Matrix, frozen, and the specific regions were punched out bilaterally with a microdissecting needle (gauge 0.5 mm) under a stereomicroscope. For each region, we took samples every 4 hours, starting at ZT0 (Zeitgaber time 0; the time of lights on), for 24 hours (6 time-point samples for each region), and we pooled the samples from the different time points. We independently sampled each region twice (n=2). These samples were purified their RNA, and measured with Affymetrix GeneChip Mouse Genome 430 2.0 arrays. Expression values were then summarized with the RMA method. After several analysis with the expression data, the data and analysis results were stored in the BrainStars database. The database has a REST-like Web API interface for accessing from your Web applications. This document shows how to access the database via our Web API.

Proper citation: BrainStars (RRID:SCR_005810) Copy   

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http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/content/ocdm

To satisfy the need for standardized terminologies several ontologies, we are developing the Ontology of Craniofacial Development and Malformation. When complete, this ontology will describe several realms of anatomy and development relevant to FaceBase, including: * Human craniofacial anatomy, including developmental progressions * Craniofacial malformations * Mouse craniofacial anatomy * Mappings between mouse and human anatomy These ontologies are currently undergoing active development. As a result, these files should be considered very preliminary. They may not work correctly, and contents will almost certainly undergo significant change. Five (sub) ontologies in this zip archive correspond to the categories described above. * OCDM - Ontology of Craniofacial Development and Malformation: currently imports the CHO, CMO, and the CHMMO. * CHO - Craniofacial Human Ontoloogy: normal adult human craniofacial anatomy derived from the FMA. * CMO - Craniofacial Mouse Ontology: normal adult mouse craniofacial anatomy * CHMMO - Craniofacial Human-Mouse Mapping Ontology: mappings of classes in the * CHO to related (homologous) structures in the CMO. CFMO - Craniofacial Malformation Ontology: abnormal human anatomy, includes the CHO All ontologies are in Protege Frames format (requires Protege 3.x). Ontologies refer to other ontologies via the Protege include mechanism. The CHMMO includes the CHO and the CMO. The OCDM (which is the umbrella ontology) includes all of the rest. Future releases will include translations to the OWL language.

Proper citation: OCDM - Ontology of Craniofacial Development and Malformation (RRID:SCR_005999) Copy   

•   Source: SciCrunch Registry

http://www.brain-map.org/api/index.html

API and demo application for accessing the Allen Brain Atlas Mouse Brain data. Data available via the API includes download high resolution images, expression data from a 3D volume, 3D coordinates of the Allen Reference Atlas, and searching genes with similar gene expression profiles using NeuroBlast. Data made available includes: * High resolution images for gene expression, connectivity, and histology experiments, as well as annotated atlas images * 3-D expression summaries registered to a reference space for the Mouse Brain and Developing Mouse Brain * Primary microarray results for the Human Brain and Non-Human Primate * RNA sequencing results for the Developing Human Brain * MRI and DTI files for Human Brain The API consists of the following resources: * RESTful model access * Image download service * 3-D expression summary download service * Differential expression search services * NeuroBlast correlative searches * Image-to-image synchronization service * Structure graph download service

Proper citation: Allen Brain Atlas API (RRID:SCR_005984) Copy   

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http://mango.adult-neurogenesis.de

Database of genes concerning adult neurogenesis mapped to cell types and processes that have been curated from the literature. In its present state, the database is restricted to neurogenesis in the hippocampus.

Proper citation: Mammalian Adult Neurogenesis Gene Ontology (RRID:SCR_006176) Copy   

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https://syllabus.med.unc.edu/courseware/embryo_images/

Tutorial that uses scanning electron micrographs (SEMs) as the primary resource to teach mammalian embryology. The 3-D like quality of the micrographs coupled with selected line drawings and minimal text allow relatively easy understanding of the complex morphological changes that occur in utero. Because early human embryos are not readily available and because embryogenesis is very similar across mammalian species, the majority of micrographs that are utilized in this tutorial are of mouse embryos. The remainder are human. This tutorial is divided into units that may be studied in any order. All of the images have a legend that indicates the age of the embryo. If it is a mouse embryo, the approximate equivalent human age is indicated. To minimize labeling, color-coding is widely used. To view the micrographs without color, the cursor may be placed on the image. The SEMs used in this tutorial are from the Kathleen K. Sulik collection. The line drawings have been used with permission from Lippincott Williams & Wilkins and are from the 6th and 7th editions of Langman''s Medical Embryology by T.W. Sadler.

Proper citation: Embryo Images Normal and Abnormal Mammalian Development (RRID:SCR_006297) Copy   

•   Source: SciCrunch Registry

https://pb.apf.edu.au/phenbank/homePage.html

The NHMRC Australian PhenomeBank (APB) is a non-profit repository of mouse strains used in Medical Research. The database allows you to search for murine strains, housed or archived in Australia, carrying mutations in particular genes, strains with transgenic alterations and for mice with particular phenotypes. 1876 publicly available strains, 922 genes, 439 transgenes The APB has two roles: Provide and maintain a central database of genetically modified mice held in Australia either live or as cryopreserved material; Establish and maintain a mouse strain archive. Strains are archived as cryopreserved sperm or embryos.

Proper citation: NHMRC Australian PhenomeBank (RRID:SCR_006149) Copy   

•   Source: SciCrunch Registry

https://www.infrafrontier.eu/emma/

Non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant strains essential for basic biomedical research. Users may browse by strain, gene, phenotype, or human disease. Its primary objective is to establish and manage a unified repository for maintaining medically relevant mouse mutants and making them available to the scientific community. Therefore, EMMA archives mutant strains and distributes them to requesting researchers. EMMA also hosts courses in cryopreservation, to promote the use and dissemination of frozen embryos and spermatozoa. Dissemination of knowledge is further fostered by a dedicated resource database. Anybody who wants their mutant mouse strains cryopreserved may deposit strains with EMMA. However depositors must be aware that these strains become freely available to other researchers after being deposited.With more than 8400 mutant mouse strains and asmall but increasing number of rat mutant strains available, EMMA is the primary mouse repository in Europe and the third largest non-profit repository worldwide.

Proper citation: European Mouse Mutant Archive (RRID:SCR_006136) Copy   

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http://www.fimre.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 7, 2022. Federation of International Mouse Resources (FIMRe) is a collaborating group of Mouse Repository and Resource Centers worldwide whose collective goal is to archive and provide strains of mice as cryopreserved embryos and gametes, ES cell lines, and live breeding stock to the research community. Goals of the Federation of International Mouse Resources: * Coordinate repositories and resource centers to: ** archive valuable genetically defined mice and ES cell lines being created worldwide ** meet research demand for these genetically defined mice and ES cell lines * Establish consistent, highest quality animal health standards in all resource centers * Provide genetic verification and quality control for genetic background and mutations * Provide resource training to enhance user ability to utilize cryopreserved resources

Proper citation: Federation of International Mouse Resources (RRID:SCR_006137) Copy   

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http://www.stembase.ca

A publicly accessible database containing data on Affymetrix DNA microarray experiments, and Serial Analysis of Gene Expression, mostly on human and mouse stem cell samples and their derivatives to facilitate the discovery of gene functions relevant to stem cell control and differentiation. It has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. There is currently more than 210 stem cell samples in 60 different experiments, with more being added regularly. The samples were originated by researchers of the Stem Cell Network and processed at the Core Facility of Stemcore Laboratories under the management of Ms. Pearl Campbell in the frame of the Stem Cell Genomics Project. Periodically, new expression data is submitted to the Gene Expression Omnibus (GEO) repository at the National Center for Biotechnological Information, in order to allow researchers to compare the data deposited in StemBase to a large amount of gene expression data sets. StemBase is different from GEO in both focus and scope. StemBase is concerned exclusively with stem cell related data. we are focused in Stem Cell research. We have made a significant effort to ensure the quality and consistency of the data included. This allows us to offer more specialized analysis tools related to Stem Cell data. GEO is intended as a large scale public archive. Deposition in a public repository such as GEO is required by most important scientific journals and it is advantageous for a further diffusion of the data since GEO is more broadly used than StemBase.

Proper citation: StemBase (RRID:SCR_006252) Copy   

•   Source: SciCrunch Registry