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https://icite.od.nih.gov/covid19/search/

NIH comprehensive, curated source for publications related to COVID-19. Includes articles from PubMed and pre-prints from arXiv, medRxiv, bioRxiv, and ChemRxiv. Updated daily. NIH Office of Portfolio Analysis has developed this resource to explore and analyze set of advances in COVID‑19 research as they accumulate in real time, and complements efforts by NLM to aggregate full text documents broadly related to COVID-19 and other outbreaks, and articles on COVID‑19 specific to PubMed database.

Proper citation: NIH COVID-19 Portfolio (RRID:SCR_018295) Copy   

•   Source: SciCrunch Registry

https://datascience.nih.gov/covid-19-open-access-resources

COVID-19 open access data and computational resources provided by federal agencies, including NIH, public consortia, and private entities. Continuously updated as more information becomes available. These resources are being shared for scientific and public health interests, and content is responsibility of resource organizers.

Proper citation: Data and Computational Resources to Address COVID-19 (RRID:SCR_018274) Copy   

•   Source: SciCrunch Registry

http://glycam.org/

Web provides tools for modeling 3D structures of molecules and complexes containing carbohydrates including oligosaccharide conformation modeling and glycoprotein 3D structure modeling. Used to simplify prediction of three dimensional structures of carbohydrates and macromolecular structures involving carbohydrates.

Proper citation: GLYCAM-Web (RRID:SCR_018260) Copy   

•   Source: SciCrunch Registry

https://www.socr.umich.edu/

SOCR designs, validates and freely disseminates knowledge. The Resource develops AI/ML tools, mathematical models, and end-to-end data analytic protocols for biomedical and health studies. It provides portable online aids for probability, statistics and health science education, promotes technology enhanced instruction, supports efficient statistical computing, supports AI-services, and advances predictive big data analytics. The SOCR platform includes repository of interactive apps, datasets and case-studies, computational tools, visualization approaches, instructional resources, learning materials, and curricular components. SOCR faculty, staff, and students support data and information science collaborations and analytic partnerships involving biomedical, healthcare, and biostatistical investigations.

Proper citation: University of Michigan Statistics Online Computational Resource Core Facility (RRID:SCR_022917) Copy   

•   Source: SciCrunch Registry

https://www.cores.emory.edu/iemc/

Core helps investigators use the latest technologies on structural research in their projects. Provides expertise in experimental needs.

Proper citation: Emory University Robert P. Apkarian Integrated Electron Microscopy Core Facility (RRID:SCR_023537) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://science.education.nih.gov/SciEdBlog

A blog put out by the NIH Office of Science Education.

Proper citation: NIH SciEd Blog (RRID:SCR_005499) Copy   

•   Source: SciCrunch Registry

http://frederick.cancer.gov/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://crcview.hegroup.org/

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   

•   Source: SciCrunch Registry

https://www.pharmgkb.org/

NIH-funded resource that provides information about how human genetic variation affects response to medications. PharmGKB collects, curates and disseminates knowledge about clinically actionable gene-drug associations and genotype-phenotype relationships.

Proper citation: PharmKGB (RRID:SCR_025580) Copy   

•   Source: SciCrunch Registry

https://sparc.science/about/consortia/precision

Project titled Program to Reveal and Evaluate Cells-to-gene Information that Specify Intricacies, Origins, and Nature of Human Pain (PRECISION) Network to develop meaningful resource for knowledge transfer, and to integrate and share Human Pain Associated Genes and Cell Datasets. Building knowledge platform to visualize, query, and interact with these data will support researchers and help accelerate dissemination of vital data to the larger scientific community. These goals align with NIH Helping to End Addiction Long-term (HEAL) Initiative, which seeks to accelerate the discovery and successful translation of non-addictive pain therapeutics. PRECISION Human Pain Network will leverage prior interdisciplinary collaboration to create workflows, tools, and infrastructure to define data and metadata types, to improve data management and sharing, and to integrate datasets and visualization tools.

Proper citation: NIH PRECISION Human Pain Network (RRID:SCR_025458) 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

http://www.midasplatform.org/

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   

•   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

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   

•   Source: SciCrunch Registry

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-su-arc.se/dementia-in-swedish-twins-harmony/

A twin study characterizing the importance of genetic factors for dementia and using discordant twin pairs to study other putative risk factors which control for genetic propensity to develop the disease. Molecular genetic studies have identified a number of mutations and other markers associated with early age of onset Alzheimer''''s disease. However, most cases of late age of onset dementia are considered sporadic, that is, without a clear genetic basis. Twin studies provide a unique opportunity to characterize the importance of genetic factors for dementia. Discordant twin pairs additionally provide the opportunity to study other putative risk factors which controlling for genetic propensity to develop the disease. In the first wave of the Study of Dementia in Swedish Twins, all SATSA twins born before 1935 have been screened for dementia symptoms. Over 190 suspects have been identified. This pilot study has been expanded to the entire registry in the study known as HARMONY. All twins aged 65 and older were invited to participate in a computer assisted telephone screening interview. A total of 13,519 individuals completed the interview (response rate = 75.9%). Dementia screening was based on the TELE, which includes the 10-item MSQ, other cognitive items (counting backwards, recalling three words, and similarities), and questions about health and daily functioning; or on Blessed scores obtained from a proxy interview. Among those screened, 1565 were positive for suspicion of dementia and were referred for complete clinical evaluation by a physician and a nurse. Once the preliminary in-person evaluation suggested that the suspected case was demented, the twin partner was also invited for an identical clinical work-up. Response rate for clinical evaluations is 71.4%. Approximately half of those visited for evaluation have been diagnosed as demented according to DSM-IV criteria, of which two-thirds have Alzheimer''''s disease. An extensive assessment of probable risk exposure is also included. Longitudinal follow-up is yet another feature of the study. Association studies with candidate genes are also being performed. Types of samples * DNA Number of sample donors * 1154 (sample collection completed)

Proper citation: KI Biobank - HARMONY (RRID:SCR_008884) 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