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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.

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On page 1 showing 1 ~ 20 out of 155 results
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http://www.patternlabforproteomics.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible

Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy   


  • RRID:SCR_005212

    This resource has 1+ mentions.

http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/v-phaser-2

A software tool to call variants in genetically heterogeneous populations from ultra-deep sequence data. It combines information regarding the covariation (i.e. phasing) between observed variants to increase sensitivity and an expectation maximization algorithm that iteratively recalibrates base quality scores to increase specificity. V-Phaser can reliably detect rare variants in diverse populations that occur at frequencies of <1%. V-Phaser 2 is a complete rewrite of the original V-Phaser. It contains a new model for length polymorphisms (indels) and incorporates paired end read information in its phasing model. The data access and probability computation sections of the code have also been highly optimized, resulting in substantial improvements in running time and memory usage.

Proper citation: V-Phaser 2 (RRID:SCR_005212) Copy   


https://www.urmc.rochester.edu/microbiology-immunology/xenopus-laevis.aspx

A comprehensive resource specializing in the use of the amphibian Xenopus laevis (the African clawed frog) for biomedical and immunological research. Several genetically-defined inbred strains and clones are available for study. The facility also maintains and develops research tools such as transgenic animals, monoclonal antibodies, cell lines, DNA libraries, and molecular probes. XLRR includes a satellite facility devoted to study infectious diseases caused by iridovirus. Technical assistance, education, and training are also provided.

Proper citation: Xenopus laevis Research Resource for Immunobiology (XLRR) (RRID:SCR_014354) Copy   


  • RRID:SCR_008366

    This resource has 1+ mentions.

http://www.jax.org/imr/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2012. The function of the IMR is to select, import, cryopreserve, maintain, and distribute these important strains of mice to the research community. To improve their value for research, the IMR also undertakes genetic development of stocks, such as transferring mutant genes or transgenes to defined genetic backgrounds and combining transgenes and/or targeted mutations to create new mouse models for research. The function of the IMR is to: * select biomedically important stocks of transgenic, chemically induced, and targeted mutant mice * import these stocks into the Jackson Laboratory by rederivation procedures that rid them of any pathogens they might carry * cryopreserve embryos from these stocks to protect them against accidental loss and genetic contamination * backcross the mutation onto an inbred strain, if necessary * distribute them to the scientific community More than 1000 mutant stocks have been accepted by the IMR from 1992 through December 2006. Current holdings include models for research on cancer; breast cancer; immunological and inflammatory diseases; neurological diseases; behavioral, cardiovascular and heart diseases; developmental, metabolic and other diseases; reporter (e.g., GFP) and recombinase (e.g., cre/loxP) strains. About eight strains a month are being added to the IMR holdings. Research is being conducted on improved methods for assisted reproduction and speed congenic production. Most of the targeted mutants arrive on a mixed 129xC57BL/6 genetic background, and as many of these as possible are backcrossed onto an inbred strain (usually C57BL/6J). In addition, new mouse models are being created by intercrossing carriers of specific transgenes and/or targeted mutations. Simple sequence length polymorphism DNA markers are being used to characterize and evaluate differences between inbred strains, substrains, and embryonic stem cell lines.

Proper citation: Induced Mutant Resource (RRID:SCR_008366) Copy   


http://www.immunetolerance.org/

International clinical research consortium dedicated to the clinical evaluation of novel tolerogenic approaches for the treatment of autoimmune diseases, asthma and allergic diseases, and the prevention of graft rejection. They aim to advance the clinical application of immune tolerance by performing high quality clinical trials of emerging therapeutics integrated with mechanism-based research. In particular, they aim to: * Establish new tolerance therapeutics * Develop a better understanding of the mechanisms of immune function and disease pathogenesis * Identify new biomarkers of tolerance and disease Their goals are to identify and develop treatment game changers for tolerance modulating therapies for the treatment of immune mediated diseases and disabling conditions, and to conduct high quality, innovative clinical trials and mechanistic studies not likely to be funded by other sources or to be conducted by private industry that advance our understanding of immunological disorders. In the Immune Tolerance Network's (ITN) unique hybrid academic/industry model, the areas of academia, government and industry are integral to planning and conducting clinical studies. They develop and fund clinical trials and mechanistic studies in partnership. Their development model is a unique, interactive process. It capitalizes on their wide-ranging, multidisciplinary expertise provided by an advisory board of highly respected faculty from institutions worldwide. This model gives investigators special insight into developing high quality research studies. The ITN is comprised of leading scientific and medical faculty from more than 50 institutions in nine countries worldwide and employs over 80 full-time staff at the University of California San Francisco (UCSF), Bethesda, Maryland and Benaroya Research Institute in Seattle, Washington.

Proper citation: Immune Tolerance Network (ITN) (RRID:SCR_001535) Copy   


http://www.citisletstudy.org/

Network of clinical centers and a data coordinating center established to conduct studies of islet transplantation in patients with type 1 diabetes.

Proper citation: Clinical Islet Transplantation Consortium (CITC) (RRID:SCR_014385) Copy   


  • RRID:SCR_023241

    This resource has 100+ mentions.

https://bioconductor.org/packages/release/bioc/html/Maaslin2.html

SoftwareR package that identifies microbial taxa correlated with factors of interest using generalized linear models and mixed models.Used for efficiently determining multivariable association between clinical metadata and microbial meta'omic features.

Proper citation: MaAsLin2 (RRID:SCR_023241) Copy   


  • RRID:SCR_017139

https://github.com/EpistasisLab/ReBATE

Open source software Python package to compare relief based feature selection algorithms used in data mining. Used for feature selection in any bioinformatics problem with potentially predictive features and target outcome variable, to detect feature interactions without examination of all feature combinations, to detect features involved in heterogeneous patterns of association such as genetic heterogeneity .

Proper citation: ReBATE (RRID:SCR_017139) Copy   


http://www.nhpreagents.org

Center that facilitates the optimal use of nonhuman primate models in biomedical research by identifying, developing, characterizing and producing reagents for monitoring or modulating immune responses. They distribute non-human primate-specific antibodies for in vitro diagnostics, as well as develop and produce primate recombinant antibodies for in vivo cell depletion or modulating immune responses.

Proper citation: Nonhuman Primate Reagent Resource (RRID:SCR_012986) Copy   


https://repository.niddk.nih.gov/study/21

Data and biological samples were collected by this consortium organizing international efforts to identify genes that determine an individual risk of type 1 diabetes. It originally focused on recruiting families with at least two siblings (brothers and/or sisters) who have type 1 diabetes (affected sibling pair or ASP families). The T1DGC completed enrollment for these families in August 2009. They completed enrollment of trios (father, mother, and a child with type 1 diabetes), as well as cases (people with type 1 diabetes) and controls (people with no history of type 1 diabetes) from populations with a low prevalence of this disease in January 2010. T1DGC Data and Samples: Phenotypic and genotypic data as well as biological samples (DNA, serum and plasma) for T1DGC participants have been deposited in the NIDDKCentral Repositories for future research.

Proper citation: Type 1 Diabetes Genetics Consortium (RRID:SCR_001557) Copy   


  • RRID:SCR_002047

    This resource has 100+ mentions.

http://www.aspgd.org/

Database of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus including information about genes and proteins of Aspergillus nidulans and Aspergillus fumigatus; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Sgenus species. Also available are Gene Ontology (GO) and community resources. Based on the Candida Genome Database, the Aspergillus Genome Database is a resource for genomic sequence data and gene and protein information for Aspergilli. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). Search options allow you to: *Search AspGD database using keywords. *Find chromosomal features that match specific properties or annotations. *Find AspGD web pages using keywords located on the page. *Find information on one gene from many databases. *Search for keywords related to a phenotype (e.g., conidiation), an allele (such as veA1), or an experimental condition (e.g., light). Analysis and Tools allow you to: *Find similarities between a sequence of interest and Aspergillus DNA or protein sequences. *Display and analyze an Aspergillus sequence (or other sequence) in many ways. *Navigate the chromosomes set. View nucleotide and protein sequence. *Find short DNA/protein sequence matches in Aspergillus. *Design sequencing and PCR primers for Aspergillus or other input sequences. *Display the restriction map for a Aspergillus or other input sequence. *Find similarities between a sequence of interest and fungal nucleotide or protein sequences. AspGD welcomes data submissions.

Proper citation: ASPGD (RRID:SCR_002047) Copy   


https://med.stanford.edu/sfgf.html

Stanford Genomics formerly Stanford Functional Genomics Facility provides services for high throughput sequencing, single cell assays, gene expression and genotyping studies utilizing microarray and real time PCR, and related services. High throughput sequencing (Illumina HiSeq 4000, NextSeq 500, MiSeq and MiniSeq), microarray gene expression and genotyping services (Affymetrix, Agilent and Illumina). Provides 24/7 access to instruments, equipment and software utilized within genomics field.

Proper citation: Stanford Genomics Service Center Core Facility (RRID:SCR_002050) Copy   


  • RRID:SCR_002147

    This resource has 10+ mentions.

http://cinteny.cchmc.org/

Online database for finding and analyzing syntenic regions across multiple genomes and measuring the extent of genome rearrangement using reversal distance as a measure.

Proper citation: Cinteny (RRID:SCR_002147) Copy   


  • RRID:SCR_002767

    This resource has 1+ mentions.

http://www.macaque.org/

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 on June 8, 2020.Macaque genomic and proteomic resources and how they are providing important new dimensions to research using macaque models of infectious disease. The research encompasses a number of viruses that pose global threats to human health, including influenza, HIV, and SARS-associated coronavirus. By combining macaque infection models with gene expression and protein abundance profiling, they are uncovering exciting new insights into the multitude of molecular and cellular events that occur in response to virus infection. A better understanding of these events may provide the basis for innovative antiviral therapies and improvements to vaccine development strategies.

Proper citation: Macaque.org (RRID:SCR_002767) Copy   


  • RRID:SCR_025453

    This resource has 100+ mentions.

https://github.com/sokrypton/ColabFold

Software application offers accelerated prediction of protein structures and complexes by combining homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. Used for protein folding.

Proper citation: ColabFold (RRID:SCR_025453) Copy   


  • RRID:SCR_005398

    This resource has 10+ mentions.

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   


  • RRID:SCR_014659

    This resource has 1000+ mentions.

https://evidencemodeler.github.io/

Software tool for automated eukaryotic gene structure annotation that reports eukaryotic gene structures as weighted consensus of all available evidence. Used to combine ab intio gene predictions and protein and transcript alignments into weighted consensus gene structures. Inputs include genome sequence, gene predictions, and alignment data (in GFF3 format).

Proper citation: EVidenceModeler (RRID:SCR_014659) Copy   


https://www.niaid.nih.gov/diseases-conditions/coronaviruses

Information about coronaviruses, including COVID-19. NIAID provides research funding and resources for scientific community to facilitate development of vaccines, therapeutics, and diagnostics for infectious diseases, including those caused by coronaviruses.

Proper citation: NIAID Overview of Coronaviruses (RRID:SCR_018290) Copy   


  • RRID:SCR_021227

    This resource has 10+ mentions.

https://gitlab.com/gernerlab/cytomap/-/wikis/home

Software tool as spatial analysis software for whole tissue sections.Utilizes information on cell type and position to phenotype local neighborhoods and reveal how their spatial distribution leads to generation of global tissue architecture.Used to make advanced data analytic techniques accessible for single cell data with position information.

Proper citation: CytoMAP (RRID:SCR_021227) Copy   


  • RRID:SCR_022712

    This resource has 10+ mentions.

https://github.com/zdk123/SpiecEasi

Software R package for microbiome network analysis. Used for inference of microbial ecological networks from amplicon sequencing datasets. Combines data transformations developed for compositional data analysis with graphical model inference framework that assumes underlying ecological association network is sparse.

Proper citation: SpiecEasi (RRID:SCR_022712) Copy   



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