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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
A research- and development-oriented company based in Berlin that engineers and markets technology for animal behavior research offering unique, automated instrumentation. This includes specialized applications of virtual reality and touch screen technology for animal behavior environments and RFID (transponder) operated devices in home cage environments. Their experimental systems are used for behavioral phenotyping, brain research, experimental psychology, and the diagnostic characterization of animal models for translational medicine.
Proper citation: PhenoSys (RRID:SCR_004072) Copy
http://www.i4sa.com/web_app/main/defaultProduct.aspx?ID=82&PT=3
Magnetic resonance compatible monitoring and gating system, including software, that enables monitoring rectal temperature, electrocardiogram and respiration rate during magnetic resonance imaging scan time. The PC displays multiple waveforms, measured values, trends and gating pulses. The data Acquisition modules are controlled by menu driven software from the PC. Data acquisition modules are available to measure the following parameters: ECG, respiration (three ways), temperature (two ways), pressure including invasive blood pressure (two ways), oxygen saturation and end-tidal CO2.
Proper citation: Model 1025 MR-compatible Small Animal Monitoring and Gating System (RRID:SCR_002090) Copy
http://www.ara.com/products/mppd.htm
Computational model that can be used for estimating human and rat airway particle dosimetry. The model is applicable to risk assessment, research, and education. The MPPD model calculates the deposition and clearance of monodisperse and polydisperse aerosols in the respiratory tracts of rats and human adults and children (deposition only) for particles ranging in size from ultrafine (0.01 micrometers) to coarse (20 micrometers). The models are based on single-path and multiple-path methods for tracking air flow and calculating aerosol deposition in the lung. The single-path method calculates deposition in a typical path per airway generation, while the multiple-path method calculates particle deposition in all airways of the lung and provides lobar-specific and airway-specific information. Within each airway, deposition is calculated using theoretically derived efficiencies for deposition by diffusion, sedimentation, and impaction within the airway or airway bifurcation. Filtration of aerosols by the nose and mouth is determined using empirical efficiency functions. The MPPD model includes calculations of particle clearance in the lung following deposition.
Proper citation: Multiple-Path Particle Dosimetry Model (RRID:SCR_001486) Copy
http://www.iitcinc.com/Plantar.html
The IITC Plantar Analgesia Meter for thermal paw can be used on 12 mice, 6 rats and other animals (cats, rabbits) unrestrained when testing for narcotic drugs. Experiments are easy to perform, simply slide the test head under test subject, align the heat source via our exclusive guide light (idle state) by the attached, adjustable, angled mirror on test head to test subject and perform tests.
Proper citation: IITC Life Sciences Plantar Test Apparatus (RRID:SCR_012152) Copy
http://gmod.org/wiki/Flash_GViewer
Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool
Proper citation: Flash Gviewer (RRID:SCR_012870) Copy
http://www.iitcinc.com/rotarod.html
Kit for assessing motor function and endurance in mice and rats. IITC’s Rotarod Test is capable of having up to five mice or rats tested at a time standard.
Proper citation: IITC Life Sciences Rotarod Test (RRID:SCR_015698) Copy
http://olympus.magnet.fsu.edu/galleries/ratbrain/index.html
An image gallery of the rat brain labeled via immunofluorescence in coronal, horizontal, and sagittal thick sections using laser scanning confocal microscopy.
Proper citation: Confocal Microscopy Image Gallery - Rat Brain Tissue Sections (RRID:SCR_002432) Copy
http://services.nbic.nl/copub/portal/
Text mining tool that detects co-occuring biomedical concepts in abstracts from the MedLine literature database. It allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs.
Proper citation: CoPub (RRID:SCR_005327) Copy
http://variant.bioinfo.cipf.es/
Analysis tool that can report the functional properties of any variant in all the human, mouse or rat genes (and soon new model organisms will be added) and the corresponding neighborhoods. Also other non-coding extra-genic regions, such as miRNAs are included in the analysis. It not only reports the obvious functional effects in the coding regions but also analyzes noncoding SNVs situated both within the gene and in the neighborhood that could affect different regulatory motifs, splicing signals, and other structural elements. These include: Jaspar regulatory motifs, miRNA targets, splice sites, exonic splicing silencers, calculations of selective pressures on the particular polymorphic positions, etc. Software analysis pipelines used in the analysis of NGS data are highly modular, heterogeneous, and rapidly evolving. VARIANT can easily be incorporated into a NGS resequencing pipeline either as a CLI or invoked a webservice. It inputs data directly from the most widely used programs for SNV detection.
Proper citation: VARIANT (RRID:SCR_005194) Copy
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
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
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
Urinary kidney biomarkers (KIM-1, albumin, total protein, 2-microglobulin, cystatin C, clusterin and trefoil factor-3) that are considered acceptable biomarkers for the detection of acute drug-induced nephrotoxicity in rats and can be included along with traditional clinical chemistry markers and histopathology in toxicology studies. These biomarkers may be used voluntarily as additional evidence of nephrotoxicity in nonclinical safety assessment studies to complement the standard data (BUN and sCr). In ROC analyses, some of these biomarkers showed better sensitivity and specificity than BUN and sCr relative to histopathological alterations considered to be the gold standard when tested with a limited number of nephrotoxicant and control compounds.
Proper citation: PSTC Nephrotoxicity Biomarkers (RRID:SCR_003709) Copy
http://openconnectomeproject.org/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.
Proper citation: Open Connectome Project (RRID:SCR_004232) Copy
Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.
Proper citation: Stem Cell Commons (RRID:SCR_004415) Copy
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
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
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
Website for analyzing microarray data. Software toolbox for storing, analyzing and integrating microarray data and related genotype and phenotype data. The site is particularly suited for combining QTL and microarray data to search for candidate genes contributing to complex traits. In addition, the site allows, if desired by the investigators, sharing of the data. Investigators can conduct in-silico microarray experiments using their own and/or shared data. There are five major sections of the site: Genome/Transcriptome Data Browser, Microarray Analysis Tools, Gene List Analysis Tools, QTL Tools, and Downloads. The genome/transcriptome data browser combines a genome browser with all the microarray, RNA-Seq, and Genomic Sequencing data. This provides an effective platform to view all of this data side by side. Source code is available on GitHub.
Proper citation: PhenoGen Informatics (RRID:SCR_001613) Copy
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