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https://monarchinitiative.org/

Repository of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors, and ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in context of genetic and genomic data, using semantics and statistics. Discovery system provides basic and clinical science researchers, informaticists, and medical professionals with integrated interface and set of discovery tools to reveal genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. Database that indexes authoritative information on experimental models of disease from MGI, RGD and ZFIN.

Proper citation: MONARCH Initiative (RRID:SCR_000824) Copy   

•   Source: SciCrunch Registry

http://mbl.org

Collection of high resolution images and databases of brains from many genetically characterized strains of mice with aim to systematically map and characterize genes that modulate architecture of mammalian CNS. Includes detailed information on genomes of many strains of mice. Consists of images from approximately 800 brains and numerical data from just over 8000 mice. You can search MBL by strain, age, sex, body or brain weight. Images of slide collection are available at series of resolutions. Apple's QuickTime Plugin is required to view available MBL Movies.

Proper citation: Mouse Brain Library (RRID:SCR_001112) Copy   

•   Source: SciCrunch Registry

http://clarityresourcecenter.org/

Protocols and other training materials related to the CLARITY protocol, a technique for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable.

Proper citation: Clarity resources (RRID:SCR_001387) Copy   

•   Source: SciCrunch Registry

http://www.uc.edu/labs/mmpc.html

Research center that provides metabolic and physiologic phenotyping services for mouse models of diabetes, diabetic complications, obesity and related disorders. It specializes in the immunological aspects of Type I diabetes, measurement of various glucose and lipid metabolism parameters relevant to Type II diabetes as well as diabetic complications such as heart disease and obesity.

Proper citation: MMPC-University of Cincinnati Medical Center (RRID:SCR_015367) Copy   

•   Source: SciCrunch Registry

https://labnodes.vanderbilt.edu/mmpc

Research center whose mission is to advance research in the area of diabetes by providing experimental tools to the scientific community for phenotyping mouse transgenic models of diabetes and related disorders.

Proper citation: MMPC-Vanderbilt University School of Medicine (RRID:SCR_015374) Copy   

•   Source: SciCrunch Registry

http://neuroexpresso.org/

Database of mouse brain cell type-specific gene expression datasets. NeuroExpresso is able to demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression.

Proper citation: NeuroExpresso (RRID:SCR_015724) 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://purl.bioontology.org/ontology/PHENOMEBLAST

A cross-species phenotype and anatomy ontology resulting from combining available anatomy and phenotype ontologies and their definitions. The ontology includes phenotype definitions for yeast, mouse, fish, worm, fly and human phenotypes and diseases.

Proper citation: PhenomeBLAST Ontology (RRID:SCR_005139) Copy   

•   Source: SciCrunch Registry

https://datashare.ed.ac.uk/handle/10283/3844

Genome transcriptome atlas by RNA in situ hybridization on sagittal sections of developing mouse at embryonic day 14.5. Consists of searchable database of annotated images that can be interactively viewed. Anatomy based expression profiles for coding genes and microRNAs, tissue specific genes. Expression data generated by using human and murine tissue arrays.

Proper citation: Eurexpress (RRID:SCR_005093) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/Genes/GOBrowser

With the CGAP GO browser, you can browse through the GO vocabularies, and find human and mouse genes assigned to each term. GO data updated every few months. Platform: Online tool

Proper citation: CGAP GO Browser (RRID:SCR_005676) 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://pivotcollections.org/collection.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 4th, 2023. Mouse brains displayed in the Microsoft Silverlight PivotViewer from the Mouse Brain Library (MBL) which consist of high-resolution images of brains from many genetically characterized strains of mice. PivotViewer makes it easier to interact with massive amounts of data on the web in ways that are powerful, informative, and fun. By visualizing thousands of related items at once, users can see trends and patterns that would be hidden when looking at one item at a time. Because PivotViewer leverages Deep Zoom, it displays full, high-resolution content without long load times, while the animations and natural transitions provide context and prevent users from feeling overwhelmed by large quantities of information. This simple, inviting interaction model encourages exploration and longer audience engagement times, and applies broadly to a variety of content types.

Proper citation: MBL Pivot Collection (RRID:SCR_005506) 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.cmhd.ca/

Multidisciplinary collaboration undertaking genome-wide mutagenesis to functionally annotate the mouse genome and develop new mouse models relevant to human disease. To achieve these goals two major research platforms are carried out: Gene trapping and ENU Mutagenesis. A new challenge is faced in the post-genomic era - the assignment of biological function to the human genome sequence and projecting that assignment into understanding of human health and disease. The Centre for Modeling Human Disease (CMHD) was established to take part in the worldwide initiative to address these challenges. At the CMHD, two fundamentally different, yet complimentary methods are employed to generate mutant mouse models of human disease: chemical mutagenesis by ethylnitrosourea (ENU), and gene trap insertional mutagenesis. The Centre contributes its resources to similar international efforts and is the first of its kind in Canada. The Center is also actively developing other mutagenic strategies including pharmacologic and genetic modifier screens to dissect disease pathways, and novel mutagenic techniques using embryonic stem cells. ENU Database * Statistics for Mouse Physiological Parameters * Search Mutants by Phenotype * Search Mutants by Heritability Gene Trap Database * Search by in vitro Expression Pattern * Search by Gene Trap Sequences CMHD Members Only (must register and login) * Search Mouse Line * Histopathology * Sperm, Tissue, Slide Archiving * CMHD Database Download CMHD Services * Phenotyping * Genetic Mapping * Pathology * Pathology Service Charges

Proper citation: CMHD - Centre for Modeling Human Disease (RRID:SCR_006101) Copy   

•   Source: SciCrunch Registry

http://mmdb.iab.keio.ac.jp/

MMMDB, Mouse Multiple tissue Metabolome DataBase, is a freely available metabolomic database containing a collection of metabolites measured from multiple tissues from single mice. The datases are collected using a single instrument and not integrated from literatures, which is useful for capturing the holistic overview of large metabolomic pathway. Currently data from cerabra, cerebella, thymus, spleen, lung, liver, kidney, heart, pancreas, testis, and plasma are provided. Non-targeted analyses were performed by capillary electropherograms time-of-flight mass spectrometry (CE-TOFMS) and, therefore, both identified metabolites and unknown (without matched standard) peaks were uploaded to this database. Not only quantified concentration but also processed raw data such as electropherogram, mass spectrometry, and annotation (such as isotope and fragment) are provided.

Proper citation: MMMDB - Mouse Multiple tissue Metabolome DataBase (RRID:SCR_006064) Copy   

•   Source: SciCrunch Registry

http://isaac.bioapps.biozentrum.uni-wuerzburg.de/isaac/modules/genome/species.xhtml

Web based tool to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. One can switch back to previous states and perform new analyses. Sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. Sets as well as results of analyses can be exchanged between members of groups.

Proper citation: InterSpecies Analysing Application using Containers (RRID:SCR_006243) Copy   

•   Source: SciCrunch Registry

http://www.mouseimaging.ca/

A unique resource and comprehensive imaging facility combining the latest state-of-the-art digital medical imaging technologies for the characterization of mouse functional genomics. The goals of the Mouse Imaging Centre are: * To provide a variety of medical imaging technologies adapted to studying genetically modified mice. These technologies include magnetic resonance (MR) imaging, micro computed tomography (micro-CT), ultrasound biomicroscopy (UBM), and optical projection tomography (OPT). * To screen large numbers of mice for models of human diseases. * To image an individual mouse over time to observe development, disease progression and responses to experimental treatment. * To develop an exciting team of investigators with expertise in imaging techniques, computer science, engineering, imaging processing, developmental biology and mouse pathology. * To work by collaboration with researchers throughout the world. When we look for human diseases in the human population, we make extensive use of medical imaging. Therefore, it makes sense to have available the same imaging capabilities as we investigate mice for models of human disease. The Mouse Imaging Centre (MICe) has developed high field magnetic resonance imaging microscopy, ultrasound biomicroscopy, micro computed tomography, and optical techniques. With these imaging tools, MICe is screening randomly mutagenized mice to look for phenotypes that represent human diseases and is taking established human disease models in mice and using imaging to follow the progression of disease and response to treatment over time. It is clear that imaging has a major contribution to make to phenotyping genetic variants and to characterizing mouse models. MICe is staffed by an exciting new team of about 30 investigators with expertise in imaging techniques, computer science, engineering, imaging processing, developmental biology and mouse pathology. The Mouse Imaging Centre (MICe) is not a fee-for-service facility but works through collaborations. Services include: * Projects involving MicroCT are available as a fee for service. * We will eventually move to the same model above with MRI. * Ultrasound Biomicroscopy is used for cardiac, embryo and cancer studies and is available as fee for service at $100 per study or in some cases on a collaborative basis. * Optical Projection Tomography has only limited availability on a collaborative basis. Mouse Atlas As our images are inherently three-dimensional, we will be able to make quantitative measures of size and volume. With this in mind, we are developing a mouse atlas showing the normal deviation of organ sizes. This atlas is an important resource for biologists as it has the potential to eliminate the need to sacrifice as many controls when making comparisons with mutants. Mouse Atlas Examples: * Variational Mouse Brain Atlas * Cerebral Vascular Atlas of the CBA Mouse * Neuroanatomy Atlas of the C57Bl/6j Mouse * Vascular Atlas of the Developing Mouse Embryo * Micro-CT E15.5 Mouse Embryo Atlas

Proper citation: MICe - Mouse Imaging Centre (RRID:SCR_006145) Copy   

•   Source: SciCrunch Registry

http://www.creline.org/

The CREATE consortium represents a core of major European and international mouse database holders and research groups involved in conditional mutagenesis, primarily to develop a strategy for the integration and dissemination of Cre driver strains for modelling aspects of complex human diseases in the mouse. Collectively the participants have amassed a significant number of these strains in their respective databases. Therefore one of the goals of CREATE is to provide a unified portal for worldwide access to these critical resources. The portal can either be searched through an advanced BioMart interface, by driver name, or by anatomical site of expression using Embryonic Mouse Anatomy Project (EMAP) and Mouse Anatomy (MA) ontology terms. Search results link back to the original source of the data for more detailed information and to IMSR to order mice if available. The ontology browser is particularly useful as it enables the CREATE consortium to identify cell and tissues that are not currently covered by existing lines. CREATE also aims to coordinate the production of suitable lines by the Cre generation projects described above. Through the CREATE portal, the CREATE consortium aims to develop a strategy for the production, integration and dissemination of new Cre driver strains for modelling aspects of complex human diseases in the mouse. CREATE is also developing a roadmap for harnessing emerging technologies and methods for improving Cre-mediated recombination in vivo through targeted, intensive workshops and discussion forums on the portal. This will entail review of construct design options for classical transgenic constructs (promoter/enhancer used, small size <2025 Kb) vs large transgenic constructs (BAC, P1, YAC etc.); methods used for Cre transgenic lines including random vs targeted integration, position independent expression loci, or replacement of endogenous coding sequences with Cre recombinase under the control of the endogenous locus. CREATE provides a platform for discussion of additional issues specific to inducible Cre strategies including background activity before induction, inducibility (kinetics), efficiency, and protocols used for induction of Cre recombinase activity. Additional components of the technology roadmap will be the cataloguing of other existing methodologies (rtTA, FLP, Dre) of mouse genome modification, sharing information on validated Cre mutant lines as well as identification and assessment of new methods of mutagenesis such as RNAi and other emerging technologies. Other discussion topics addressed through surveys on the CREATE portal include the characterization of Cre lines (specificity of expression/deletion; efficiency of expression/ deletion; reproducibility of deletion from animal to animal for the same floxed allele; reproducibility with different floxed alleles; timing of expression/deletion, etc.), the extent to which Cre expression changes upon backcrossing to specific genetic backgrounds through variegation and silencing; potential phenotypes caused by either integration- mediated mutagenesis or Cre ''toxicity''; and other factors affecting the specificity of Cre-mediated expression/deletion. CREATE regularly integrates common fields from the Cre-X, CreZOO and the MGI recombinase portal resources described below. The data in common consists of: * Transgene or Knock-in name. * MGI ID of allele. * Driver. * Anatomical site of expression. * Pubmed ID. * IMSR strain name and link. * Inducibility (YES/NO).

Proper citation: CREATE (RRID:SCR_006133) 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://embryoimaging.org/

Collection of high resolution images and movies of mouse and human embryos produced using high resolution episcopic microscopy (HREM). Each data set is a series of block-face images generated during sectioning through an entire embryo, typically cut at 2-3 micrometers. Datasets are organized by approximate developmental stage and each embryo has been assigned a specimen ID (SID) for identification. This is an ongoing project funded by the Wellcome Trust to provide comprehensive imaging of normal and mutant mouse embryos that will complement the standard anatomical texts and form the basis for systematic phenotyping. * Movies: A 3D reconstruction shows each embryo, and lower resolution movies created through each orthogonal plane enable you to quickly review the data set. * Image Stacks: In the stack viewer, you can step through the images in sequence, zoom in to see fine details and adjust the image contrast. * NEW: Embryo Comparison: Two image stacks can now be compared in the stack viewer.

Proper citation: Embryo Imaging (RRID:SCR_006329) Copy   

•   Source: SciCrunch Registry