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http://aidb.crbs.ucsd.edu

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented October 4, 2017.

A sub-project of the Cell Centered Database (http://ccdb.ucsd.edu) providing a public repository for animal imaging data sets from MRI and related techniques. The public AIDB website provides the ability for browsing, visualizing and downloading the animal subjected MRI data. The AIDB is a pilot project to serve the current need for public imaging repositories for animal imaging data. The Cell Centered Database (CCDB) is a web accessible database for high resolution 2D, 3D and 4D data from light and electron microscopy. The AIDB data model is modified from the basic model of the CCDB where microscopic images are combined to make 2D, 3D and 4D reconstructions. The CCDB has made available over 40 segmented datasets from high resolution magnetic resonance imaging of inbred mouse strains through the prototype AIDB. These data were acquired as part of the Mouse BIRN project by Drs. G. Allan Johnson and Robert Williams. More information about these data can be found in Badea et al. (2009) (Genetic dissection of the mouse CNS using magnetic resonance microscopy - Pubmed: 19542887)

Proper citation: Animal Imaging Database (RRID:SCR_008002) Copy   

•   Source: SciCrunch Registry

http://www.mouseatlas.org/

A portal to the Mouse Atlas of Gene Expression Project and Dissecting Gene Expression Networks in Mammalian Organogenesis Project. This Atlas will define the normal state for many tissues by determining, in a comprehensive and quantitative fashion, the number and identity of genes expressed throughout development. The resource will be comprehensive, quantitative, and publicly accessible, containing data on essentially all genes expressed throughout select stages of mouse development. Serial Analysis of Gene Expression (SAGE) is the gene expression methodology of choice for this work. Unlike expressed sequence tags (ESTs) and gene chip data, SAGE data are independent of prior gene discovery and are quantitative. Furthermore, SAGE data are digital, easily exchanged between laboratories for comparison and can be added to by scientists for years to come. Thus, this Atlas will include a data structure and data curation strategy that will facilitate the ongoing collection of gene expression data, even after the completion of this project. The Mouse Atlas project compromises 202 SAGE Libraries from 198 tissues. The list of libraries is available in a number of different groupings, including groups of libraries taken from specific tissue locations and libraries taken from specific developmental stages. Furthermore, this atlas will assemble gene expression profiles for a few focused experiments that will test hypotheses related to the techniques employed, tumor models and models of abnormal development. This will test the resource and provide quality control, validation and demonstrate applicability. Additionally, The Mammalian Organogenesis - Regulation by Gene Expression Networks (MORGEN) project will provide a complete, permanent, and accurate picture of mouse gene expression in the heart (atrioventricular canal and outflow tract), pancreas, and liver; new techniques to understand the interplay of proteins governing the expression of genes key to the development of these organ systems; and the identification of the master regulatory switches that control development of the tissues.

Proper citation: Mouse Gene Expression at the BC Cancer Agency (RRID:SCR_008091) Copy   

•   Source: SciCrunch Registry

http://mousemutant.jax.org/index.html

Producer and supplier of a collection of mice bearing spontaneous mutations. These mice contribute to a better understanding of the genetic bases of neurological, neuromuscular, sensory, metabolic, skeletal/craniofacial and developmental disorders and conditions such as diabetes, obesity and heart disease.

Proper citation: Mouse Mutant Resource (RRID:SCR_008367) Copy   

•   Source: SciCrunch Registry

http://genes2mind.org

genes2mind is a tool for rapid exploratory analysis of psychotropic drug-induced gene expression in the brain. We present here an open resource containing comparison of effects of various classes of psychotropic drugs on transcriptional alterations of ~20,000 genes in the mouse brain (C57BL/6J). Data stored in the database include raw gene expression values as well as results of drug comparison. * Genomic Signature Identification section allows for the identification of drug-specific genomic signatures. * Genomic Signature Analysis section allows for further inspection and visualization of the signatures using multidimensional data analysis (PCA), co-expression analysis and heatmaps. * Single Gene Inspection allows for brief review of expression of specific candidate genes using barplots.

Proper citation: genes2mind (RRID:SCR_008872) Copy   

•   Source: SciCrunch Registry

http://www.3dbar.org

Software package for reconstructing three-dimensional models of brain structures from 2-D delineations using a customizable and reproducible workflow. 3dBAR also works as an on-line service (http://service.3dbar.org) offering a variety of functions for the hosted datasets: * downloading reconstructions of desired brain structures in predefined quality levels in various supported formats as well as created using customizable settings, * previewing models as bitmap thumbnails and (for webGL enabled browsers) interactive manipulation (zooming, rotating, etc.) of the structures, * downloading slides from available datasets as SVG drawings. 3dBAR service can also be used by other websites or applications to enhance their functionality. * Operating System: Linux * Programming Language: Python * Supported Data Format: NIfTI-1, Other Format, VRML

Proper citation: 3DBar (RRID:SCR_008896) Copy   

•   Source: SciCrunch Registry

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

The Edwards lab conducts research in various aspects of computational biology and bioinformatics, particularly proteomics and mass spectrometry informatics and DNA and protein based signatures for pathogen detection. Some tools provided by Edwards Lab are the PepArML Meta-Search Engine, PeptideMapper Web-Service, Peptide Sequence Databases, Rapid Microorganism Identification Database (RMIDb), and GlycoPeptideSearch. Our primary area of research is the analysis of mass spectrometry experiments for proteomics. Proteomics, the qualitative and quantitative analysis of the expressed proteins of a cell, makes it possible to detect and compare the protein abundance profiles of different samples. Proteins observed to be under or over expressed in disease samples can lead to diagnostic markers or drug targets. The observation of mutated or alternatively spliced protein isoforms may provide domain experts with clues to the mechanisms by which a disease operates. The detection of proteins by mass spectrometry can even signal the presence of airborne microorganisms, such as anthrax, in the detect-to-protect time-frame. Recent research has focused on the discovery of novel peptides in proteomics datasets, improving the sensitivity and specificity of peptide identification using spectral matching with hidden Markov models, and unsupervised machine-learning based peptide identification result combining. Outside of proteomics, we work on computational tools for the design of highly specific oligonucleotides useful for pathogen signatures and PCR assay design. Recent research has focused on precomputing all human oligos of length 20 that are unique up to 4 string edits; and all bacterial 20-mer oligos that are species specific up to 4 string edits.

Proper citation: Edwards Lab (RRID:SCR_008860) Copy   

•   Source: SciCrunch Registry

http://akt.ucsf.edu/EGAN/

Exploratory Gene Association Networks (EGAN) is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, iHOP, Google, etc.). EGAN functions as a module for exploratory investigation of analysis results from multiple high-throughput assay technologies, including but not limited to: * Transcriptomics via expression microarrays or RNA-Seq * Genomics via SNP GWAS or array CGH * Proteomics via MS/MS peptide identifications * Epigenomics via DNA methylation, ChIP-on-Chip or ChIP-Seq * In-silico analysis of sequences or literature EGAN has been built using Cytoscape libraries for graph visualization and layout, and is comparable to DAVID, GSEA, Ingenuity IPA and Ariadne Pathway Studio. There are pre-collated EGAN networks available for human (Homo sapiens), mouse (Mus musculus), rat (Rattus norvegicus), chicken (Gallus gallus), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), nematode (Caenorhabditis elegans), mouse-ear cress (Arabidopsis thaliana), rice (Oryza sativa) and brewer's yeast (Saccharomyces cerevisiae). There is now an EGAN module available for GenePattern (human-only). Platform: Windows compatible, Mac OS X compatible, Linux compatible

Proper citation: EGAN: Exploratory Gene Association Networks (RRID:SCR_008856) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ABA-AMB

Allen Brain Atlas P56 Mouse Ontology

Proper citation: ABA Adult Mouse Brain Ontology (RRID:SCR_010286) 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

http://mouse.brain-map.org/static/brainexplorer

Atlas of the brain and the disorders affecting it, aimed at general practitioners and specialists in training. It consists of three main parts: a description of the different parts of the normal brain and their functions, a description of the process of neurological control, and a description of 14 different brain disorders in psychiatry and neurology - as well as their cause, symptoms, and treatment.

Proper citation: Brain Explorer Atlas and Teaching Tool (RRID:SCR_013022) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/searches/anatdict_form.shtml

For each developmental stage (using the staging system defined by Theiler), the Mouse Anatomical Dictionary organizes the terms hierarchically from body region or system to tissue to tissue substructure. Modeling the anatomy hierarchically makes it possible to record expression results from assays with differing spatial resolution in a consistent and integrated manner. The Mouse Anatomical Dictionary Browser lets you navigate the extensive dictionary hierarchies for the different developmental stages, locate specific anatomical structures within those hierarchies, and see the expression results associated with those structures. Stages 1 through 26 (embryonic development) are being developed at the Department of Biomedical Sciences, University of Edinburgh, Scotland and the MRC Human Genetics Unit, Edinburgh, as part of The Mouse Atlas and 3D Graphical Gene Expression Database Project. Stage 28 (postnatal mouse) is being developed by the Gene Expression Database Project at The Jackson Laboratory.

Proper citation: Mouse Anatomical Dictionary Browser (RRID:SCR_012778) 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

https://www.nitrc.org/projects/localizoom/

Web application for displaying high-resolution image series coupled with overlaid atlas delineations. Online pan-and-zoom type viewer with three operating modes: Display series with atlas overlay, both linear and nonlinear alignments are supported; Create or edit nonlinear alignments; Create markup which can be exported as MeshView point clouds or to Excel for further numerical analysis.

Proper citation: LocaliZoom (RRID:SCR_023481) Copy   

•   Source: SciCrunch Registry

https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   

•   Source: SciCrunch Registry

http://www.genepaint.org/MapP56_01.htm

Abbreviated reference atlas for the P56 mouse. All sections were nissl stained and digitized. To assist in the initial identification of sites of gene expression sites, maps of brains are available for E15.5, P7 and the adult. These maps depict the boundaries of major brain regions (cortex, thalamus, striatum, globus pallidus, ventral striatum, septum, basal forebrain, hippocampus, midbrain, pons, medulla, cerebellum) and also show the more prominent nerve tracts. Maps are most efficiently used by placing the window depicting the map of interest next to the gene expression image. Browsing is permitted between planes of sectioning thus allowing the most appropriate plane to be selected. Abbreviations are found in a list accessed by clicking the see abbreviation link at the bottom of each map. Alternatively, passing the cursor directly across the abbreviation on the map will result in the appearance of the appropriate term in the rider on top of the map panel. The annotation of anatomical details such as brain nuclei is currently beyond the scope of the GenePaint database. Hence, such information on the anatomy of the brain and embryo should be obtained from published atlases of mouse anatomy (Kaufman, 1995; Paxinos and Franklin, 2001; Jacobowitz and Abbott, 1997; Schambra et al., 1992; Valverde1998).

Proper citation: GenePaint P56 Mouse Atlas (RRID:SCR_002788) Copy   

•   Source: SciCrunch Registry