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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.
http://www.type2diabetesgenetics.org/
Portal and database of DNA sequence, functional and epigenomic information, and clinical data from studies on type 2 diabetes and analytic tools to analyze these data. .Provides data and tools to promote understanding and treatment of type 2 diabetes and its complications. Used for identifying genetic biomarkers correlated to Type 2 diabetes and development of novel drugs for this disease.
Proper citation: Accelerating Medicines Partnership Type 2 Diabetes Knowledge Portal (AMP-T2D) (RRID:SCR_003743) Copy
https://simtk.org/home/rna-viz-proto
A software application for animating and visualising RNA and other macromolecular structures. Users are able to use their intuition to interactively refold RNA structures and produce morphs from one structure to another. It allow researchers to explore and manipulate molecular structures Imported from BiositeMaps registry, to better understand structure:function relationships, folding pathways, and molecular motion.
Proper citation: ToRNADo (RRID:SCR_002706) Copy
Website for brain experimental data and other resources such as stimuli and analysis tools. Provides marketplace and discussion forum for sharing tools and data in neuroscience. Data repository and collaborative tool that supports integration of theoretical and experimental neuroscience through collaborative research projects. CRCNS offers funding for new class of proposals focused on data sharing and other resources.
Proper citation: CRCNS (RRID:SCR_005608) Copy
http://www.ncbi.nlm.nih.gov/pubmedcommons/
A forum where authors who have published in PubMed may comment on any publication in PubMed. Members of PubMed Commons are not anonymous and must agree to certain terms and guidelines concerning appropriate and inapproriate comments.
Proper citation: Pubmed Commons (RRID:SCR_014021) Copy
https://www.pathology.umn.edu/research/liver-tissue-cell-distribution-system
Tissue bank that provides human liver tissue from regional centers for distribution to scientific investigators throughout the United States. These USA regional centers have active liver transplant programs with human subjects approval to provide portions of the resected pathologic liver for which the transplant is performed.
Proper citation: Minnesota Liver Tissue Cell Distribution System (RRID:SCR_004840) Copy
http://udn.nichd.nih.gov/brainatlas_home.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 1, 2019. The first brain atlas for the common marmoset to be made available since a printed atlas by Stephan, Baron and Schwerdtfeger published in 1980. It is a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. For the present atlas, an adult female was perfused through the heart with PBS followed by 10% formalin. The brain was then sent to Neuroscience Associates of Knoxville, TN, who prepared the brain for histological analysis. The brain was cut in the coronal (frontal) plane at 40 microns, every sixth section stained for Nissl granules with thionine and every seventh section stained for myelinated fibers with the Weil technique. The mounted sections were photographed at the NIH (Medical Arts and Photography Branch). The equipment used was a Nikon Multiphot optical bench with Zeiss Luminar 100 mm lens, and scanned with a Better Light 6100 scan back driven by Better Light Viewfinder 5.3 software. The final images were saved as arrays of 6000x8000 pixels in Adobe Photoshop 6.0. A scale in mm provided with these images permitted construction of the final Nissl atlas files with a horizontal and vertical scale. Some additional re-touching (brightness and contrast) was done with Adobe Photoshop Elements 2.0. The schematic (labeled) atlas plates were created from the Nissl images. The nomenclature came almost exclusively from brainmaps.org, where a rhesus monkey brain with structures labeled can be found. The labels for the MRI images were placed by M. R. Zametkin, under supervision from Dr. Newman.
Proper citation: Brain atlas of the common marmoset (RRID:SCR_005135) Copy
http://llama.mshri.on.ca/funcassociate/
A web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 37 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff. A new version of FuncAssociate supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented. Platform: Online tool
Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) Copy
A federally funded research and development center dedicated to biomedical research. NCI-Frederick partners with university, government, and corporate scientists to speed the translation of laboratory research into new diagnostic tests and treatments for cancer and HIV/AIDS. NCI-Frederick is comprised of more than 2,800 government- and contractor-employed biomedical researchers, laboratory technicians, and support staff and several cancer research centers. The FNLCR provides quick response capabilities and meets special long-term research and development needs for NCI that cannot be met as effectively by existing in-house or contractor resources.
Proper citation: NCI-Frederick (RRID:SCR_004880) Copy
Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.
Proper citation: CRCView (RRID:SCR_007092) Copy
http://www.nihclinicalcollection.com
A plated array of approximately 450 small molecules that have a history of use in human clinical trials. The collection was assembled by the National Institutes of Health (NIH) through the Molecular Libraries Roadmap Initiative as part of its mission to enable the use of compound screens in biomedical research. Similar collections of FDA approved drugs have proven to be rich sources of undiscovered bioactivity and therapeutic potential. The clinically tested compounds in the NCC are highly drug-like with known safety profiles. These compounds can provide excellent starting points for medicinal chemistry optimization and, for high-affinity targets, may even be appropriate for direct human use in new disease areas.
Proper citation: NIH Clinical Collection (RRID:SCR_007349) Copy
https://commonfund.nih.gov/hmp/
NIH Project to generate resources to characterize the human microbiota and to analyze its role in human health and disease at several different sites on the human body, including nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract using metagenomic and traditional approach to genomic DNA sequencing studies.HMP was supported by the Common Fund from 2007 to 2016.
Proper citation: Human Microbiome Project (RRID:SCR_012956) Copy
https://github.com/YuanXue1993/SegAN
Image analysis software for medical image segmentation. The software is fueled by an end-to-end adversarial neural network that generates segmentation label maps.
Proper citation: SegAN (RRID:SCR_016215) Copy
Nonhuman Primate reference transcriptome resource consisting of deep sequencing complete transcriptomes (RNA-seq) from multiple NHP species.
Proper citation: Nonhuman Primate Reference Transcriptome Resource (RRID:SCR_017534) Copy
Project to create complete mesoscale connectivity atlas of the C57Black/6 mouse brain and to subsequently generate its global neural networks.
Proper citation: Mouse Connectome Project (RRID:SCR_017313) Copy
https://metagenote.niaid.nih.gov/
Quick and intuitive way to annotate data from genomics studies including microbiome. Project to aid researchers in applying standardized metadata describing what, where, how, and when of samples collected in genomics study. Collection of METAdata of GEnomics studies on web based NOTEbook. Metadata are stored in centralized repository and validated according to guidelines from Genomics Standard Consortium, which are also supported by repositories and large microbiome initiatives such as NCBI, European Bioinformatics Institute (EBI), and Earth Microbiome Project. Upon request from researchers, data will also be submitted for publication via NCBI Sequence Read Archive (SRA) repository.
Proper citation: METAGENOTE (RRID:SCR_018494) Copy
http://www.project-redcap.org/
Web application that allows users to build and manage online surveys and databases. Using REDCap's stream-lined process for rapidly developing projects, you may create and design projects using 1) the online method from your web browser using the Online Designer; and/or 2) the offline method by constructing a "data dictionary" template file in Microsoft Excel, which can be later uploaded into REDCap. Both surveys and databases (or a mixture of the two) can be built using these methods. REDCap provides audit trails for tracking data manipulation and user activity, as well as automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R). Also included are a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as branching logic, file uploading, and calculated fields. REDCap has a quick and easy software installation process, so that you can get REDCap running and fully functional in a matter of minutes. Several language translations have already been compiled for REDCap (e.g. Chinese, French, German, Portuguese), and it is anticipated that other languages will be available in full versions of REDCap soon. The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by researchers at REDCap partner institutions.
Proper citation: REDCap (RRID:SCR_003445) Copy
Web based collaborative text annotation tool. Used for managing multi-user, multi-label document annotation. Project managers can specify annotation schema for entities and relations and select annotators and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. Displays figures from full text.
Proper citation: TeamTat (RRID:SCR_023439) Copy
Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.
Proper citation: Midas Platform (RRID:SCR_002186) Copy
https://ncats.nih.gov/grdr/rdhub
A database of biospecimens collected, stored, and distributed by biorepositories in the United States and around the globe. Its goals are: To help and assist interested parties and investigators search, locate, and identify desired biospecimens needed for their research; to facilitate collaboration and sharing of material and data among investigators across the globe; to accelerate research to facilitate the discovery of new treatments, therapeutics and eventually cures for rare diseases as well as common diseases; to identify, locate and increase the awareness of existing biorepositories across the globe; and to link the RD-HUB with the Global Rare Diseases Patient Registry and Data Repository (GRDR).
Proper citation: Biospecimens/Biorepositories: Rare Disease-HUB (RD-HUB) (RRID:SCR_004327) Copy
The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.
Proper citation: LONI MiND (RRID:SCR_004820) Copy
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