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http://ccr.coriell.org/Sections/Collections/USIDNET/?SsId=15

The USIDNET DNA and Cell Repository has been established as part of an NIH-funded program - the US Immunodeficiency Network - to provide a resource of DNA and functional lymphoid cells obtained from patients with various primary immunodeficiency diseases. These uncommon disorders include patients with defects in T cell, B cell and/or granulocyte function as well as patients with abnormalities in antibodies / immunoglobulins, complement and other host defense mechanisms. All samples in this Repository have been de-identified to protect the privacy of the individual donors. The USIDNET also operates a Patient Data Registry in addition to this Repository and certain clinical data relating to a specific sample may be available through the Registry for some of the patient samples in the Repository collection. Materials in the collection are being made available at modest cost to qualified investigators in academic and commercial organizations in an effort to stimulate research to increase understanding of these orphan diseases and to promote development of new treatments. Requestors are required to complete a Statement of Research Intent briefly describing their proposed use of materials obtained from the Repository and must sign an Assurance agreeing to conditions established by USIDNET for distribution of samples from its collection. Requestors wishing to obtain additional clinical data specific to individual samples in the Repository collection must make a separate application for that information to the Registry (see www.usidnet.org) Physicians or Patients wishing to submit cell samples for the Repository collection should first contact Coriell to arrange for the Repository to send them the correct sample collection tubes as well as prepaid mailers for returning the collected sample(s) to Coriell. Separate collection and shipping procedures may be involved depending on how many samples are to be shipped at one time and whether the shipment will involve freshly obtained blood or already established cell lines.

Proper citation: USIDNET DNA and Cell Repository (RRID:SCR_004661) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

•   Source: SciCrunch Registry

http://www.sph.umich.edu/csg/abecasis/CaTS

Software tool for carrying out power calculations for large genetic association studies, including two stage genome wide association studies.

Proper citation: Calculator for Association with Two Stage design (RRID:SCR_007238) Copy   

•   Source: SciCrunch Registry

https://github.com/VH-Lab/vhlab-microscopyimageanalysis-matlab

Software Matlab app for analysis of high density imaging data like that from Array Tomography.

Proper citation: vhlab-microscopyimageanalysis-matlab (RRID:SCR_024450) Copy   

•   Source: SciCrunch Registry

http://www.biosyn.com/

A commercial supplier of custom synthetic molecules. They specialize in peptides, oligonucleotides, bioconjugation, molecular biology services, proteins and specialty chemistry.

Proper citation: Bio-Synthesis (RRID:SCR_000820) Copy   

•   Source: SciCrunch Registry

https://mibig.secondarymetabolites.org/

MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.

Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy   

•   Source: SciCrunch Registry

https://www.jax.org/news-and-insights/2004/june/app-mouse-models-for-alzheimers-disease-research

An information resource about several models for mice to develop Alzheimer's-related characteristics as they age.

Proper citation: Mouse Models For Alzheimer's Disease Research (RRID:SCR_000708) Copy   

•   Source: SciCrunch Registry

http://provean.jcvi.org/

A software tool which predicts whether an amino acid substitution or indel has an impact on the biological function of a protein.

Proper citation: PROVEAN (RRID:SCR_002182) Copy   

•   Source: SciCrunch Registry

http://tvmouse.compmed.ucdavis.edu/

Educational resource to introduce users to the anatomy, physiology, histology, and pathology of the laboratory mouse, with an emphasis on the Genetically Engineered Mouse (GEM). It provides access to histological images, scanned at high resolution and browsable through Zoomify, movie loops and animations derived from MRI, correlated MRI and histology. It has CNS data but is focused on the whole body, e.g., physiological data is available for the heart in the form of wave patterns, histology, CNS, pathology, magnetic resonance imaging, neoplasms; animation, virtual histology, mouse, correlated imaging, necropsy, whole mouse. It may be useful to neuroscientists by relating brain anatomy to the rest of the body. There is a movie illustrating necropsy of the mouse. A link to a compendium of histological slices of brain neoplasms is provided under the Image Archive link. There is a CNS link under construction for anatomical system, which presumably will include detailed CT imaging. This site still appears to be under construction.

Proper citation: Visible Mouse Project (RRID:SCR_002393) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/

Registry and results database of federally and privately supported clinical trials conducted in United States and around world. Provides information about purpose of trial, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.Offers information for locating federally and privately supported clinical trials for wide range of diseases and conditions. Research study in human volunteers to answer specific health questions. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people or populations in natural settings. ClinicalTrials.gov contains trials sponsored by National Institutes of Health, other federal agencies, and private industry. Studies listed in database are conducted in all 50 States and in 178 countries.

Proper citation: ClinicalTrials.gov (RRID:SCR_002309) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/software/eegift/index.html

Implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) EEG data. This MATLAB toolbox is compatible with MATLAB 6.5 and higher.

Proper citation: Group ICA Of EEG Toolbox (RRID:SCR_002478) Copy   

•   Source: SciCrunch Registry

https://simtk.org

A National NIH Center for Biomedical Computing that focuses on physics-based simulation of biological structures and provides open access to high quality simulation tools, accurate models and the people behind them. It serves as a repository for models that are published (as well as the associated code) to create a living archive of simulation scholarship. Simtk.org is organized into projects. A project represents a research endeavor, a software package or a collection of documents and publications. Includes sharing of image files, media, references to publications and manuscripts, as well as executables and applications for download and source code. Simulation tools are free to download and space is available for developers to manage, share and disseminate code.

Proper citation: Simtk.org (RRID:SCR_002680) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/foldvillin

An archive of hundreds of all-atom, explicit solvent molecular dynamics simulations that were performed on a set of nine unfolded conformations of a variant of the villin headpiece subdomain (HP-35 NleNle). It includes scripts for accessing the archive of villin trajectories as well as a VMD plug-in for viewing the trajectories. In addition, all starting structures used in the trajectories are also provided. The simulations were generated using a distributed computing method utilizing the symmetric multiprocessing paradigm for individual nodes of the Folding_at_home distributed computing network. The villin trajectories in the archive are divided into two projects: PROJ3036 and PROJ3037. PROJ3036 contains trajectories starting from nine non-folded configurations. PROJ3037 contains trajectories starting from the native (folded) state. Runs 0 through 8 (in PROJ3036) correspond to starting configurations 0 through 8 discussed in the paper in J. Mol. Biol. (2007) 374(3):806-816 (see the publications tab for a full reference), whereas RUN9 uses the same starting configuration as RUN8. Each run contains 100 trajectories (named clone 0-99), each with the same starting configuration but different random velocities. Trajectories vary in their length of time and are subdivided into frames, also known as a generation. Each frame contains around 400 configurational snapshots, or timepoints, of the trajectory, with the last configurational snapshot of frame i corresponding to the first configurational snapshot of generation i+1. The goal is to allow researchers to analyze and benefit from the many trajectories produced through the simulations.

Proper citation: Molecular Simulation Trajectories Archive of a Villin Variant (RRID:SCR_002704) Copy   

•   Source: SciCrunch Registry

https://dpcpsi.nih.gov/onr/nrcc

Coordinates nutritional sciences-related research and research training across the National Institutes of Health (NIH) and among Federal Agencies by providing mechanisms to communicate research, research training, policy, and education initiatives. The DNRC facilitates the exchange of information, coordinates workshops and seminars on critical issues, encourages national and international research collaborations, and serves as the NIH primary point of contact for the Department of Health and Human Services (DHHS) and other agencies, departments, and organizations in matters pertaining to nutritional sciences and physical activity. Through its dedicated efforts to promote scientific policy reviews, innovative research, interagency collaboration, and technical advancements, the DNRC strives to define the increasing roles of nutritional sciences and physical activity in health promotion and disease prevention and treatment.

Proper citation: NIH Division of Nutrition Research Coordination (RRID:SCR_001469) Copy   

•   Source: SciCrunch Registry

http://nashua.case.edu/PathwaysWeb/Web/

An integrated software system for storing, managing, analyzing, and querying biological pathways at different levels of genetic, molecular, biochemical and organismal detail. The system contains a pathways database and associated tools to store, compare, query, and visualize metabolic pathways. The aim is to develop an integrated database and the associated tools to support computational analysis and visualization of biochemical pathways. At the computational level, PathCase allows users to visualize pathways in multiple abstraction levels, and to pose predetermined and ad hoc queries using a graphical user interface. Pathways are represented as graphs, and implemented as a relational database. The available functional annotations include the identity of the substrate(s), product(s), cofactors, activators, inhibitors, enzymes or other processing molecules, GO-categories of enzymes (as well as GO hierarchy visualizations two-way-linked to PathCase enzymes), EC number information and the associated links, and synonyms and encoding genes of gene products.

Proper citation: PathCase Pathways Database System (RRID:SCR_001835) Copy   

•   Source: SciCrunch Registry

http://videocast.nih.gov/

VideoCasting of special NIH events, seminars, conferences, meetings and lectures available to viewers on the NIH network and the Internet from the VideoCast web site. VideoCasting is the method of electronically streaming digitally encoded video and audio data from a server to a client. VideoCast is often referred to as streaming video. Streaming files are not downloaded, but rather are broadcast in a manner similar to television broadcasts. The videos are processed by a compression program into a streaming format and delivered in a staggered fashion to minimize impact upon the network and maximize the experience of the content for the viewer. When users request a streaming file they will receive an initial burst of data after a short delay (file latency). While content is being viewed, the streaming server machine and software continues to stream data in such a manner that the viewer experiences no break in the content. CIT can broadcast your seminar, conference or meeting live to a world-wide audience over the Internet as a real-time streaming video. The event can be recorded and made available for viewers to watch at their convenience as an on-demand video or a downloadable podcast. CIT can also broadcast NIH-only or HHS-only content.

Proper citation: NIH VideoCasting (RRID:SCR_001885) Copy   

•   Source: SciCrunch Registry

http://www.metabolomicsworkbench.org

Repository for metabolomics data and metadata which provides analysis tools and access to various resources. NIH grantees may upload data and general users can search metabolomics database. Provides protocols for sample preparation and analysis, information about NIH Metabolomics Program, data sharing guidelines, funding opportunities, services offered by its Regional Comprehensive Metabolomics Resource Cores (RCMRC)s, and training workshops.

Proper citation: Metabolomics Workbench (RRID:SCR_013794) Copy   

•   Source: SciCrunch Registry

http://www.geworkbench.org

geWorkbench (genomics Workbench) is a Java-based open-source platform for integrated genomics. Using a component architecture it allows individually developed plug-ins to be configured into complex bioinformatic applications. At present there are more than 70 available plug-ins supporting the visualization and analysis of gene expression and sequence data. Example use cases include: * loading data from local or remote data sources. * visualizing gene expression, molecular interaction networks, protein sequence and protein structure data in a variety of ways. * providing access to client- and server-side computational analysis tools such as t-test analysis, hierarchical clustering, self organizing maps, regulatory networks reconstruction, BLAST searches, pattern/motif discovery, etc. * validating computational hypothesis through the integration of gene and pathway annotation information from curated sources as well as through Gene Ontology enrichment analysis. geWorkbench is the Bioinformatics platform of MAGNet, the National Center for the Multi-scale Analysis of Genomic and Cellular Networks (one of the 7 National Centers for Biomedial Computing funded through the NIH Roadmap). Additionally, geWorkbench is supported by caBIG, NCI''s cancer Biomedical Informatics Grid initiative.

Proper citation: genomics Workbench (RRID:SCR_013599) Copy   

•   Source: SciCrunch Registry

http://chavi-id.org

A consortium whose goal is to further HIV research and accelerate the development of a preventative HIV vaccine. Its main research target is to define immunogens and immunization regimens that induce sustained HIV cross-protective B cell and CD4+ T cell responses.

Proper citation: CHAVI-ID (RRID:SCR_014047) Copy   

•   Source: SciCrunch Registry

https://datajoint.org/

MATLAB and Python 3 high-level programming interface for MySQL databases to support data processing chains in science labs. Specifically designed to provide robust and intuitive data model for scientific data processing chains.Used for scientific data pipelines and workflow management.

Proper citation: DataJoint (RRID:SCR_014543) Copy   

•   Source: SciCrunch Registry