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http://www.patricbrc.org/portal/portal/patric/Home

A Bioinformatics Resource Center bacterial bioinformatics database and analysis resource that provides researchers with an online resource that stores and integrates a variety of data types (e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data) and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. The PATRIC project includes three primary collaborators: the University of Chicago, the University of Manchester, and New City Media. The University of Chicago is providing genome annotations and a PATRIC end-user genome annotation service using their Rapid Annotation using Subsystem Technology (RAST) system. The National Centre for Text Mining (NaCTeM) at the University of Manchester is providing literature-based text mining capability and service. New City Media is providing assistance in website interface development. An FTP server and download tool are available.

Proper citation: Pathosystems Resource Integration Center (RRID:SCR_004154) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

http://vbrc.org/index.asp

One of eight Bioinformatics Resource Centers nationwide providing comprehensive web-based genomics resources including a relational database and web application supporting data storage, annotation, analysis, and information exchange to support scientific research directed at viruses belonging to the Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, Paramyxoviridae, Poxviridae, and Togaviridae families. These centers serve the scientific community and conduct basic and applied research on microorganisms selected from the NIH/NIAID Category A, B, and C priority pathogens that are regarded as possible bioterrorist threats or as emerging or re-emerging infectious diseases. The VBRC provides a variety of analytical and visualization tools to aid in the understanding of the available data, including tools for genome annotation, comparative analysis, whole genome alignments, and phylogenetic analysis. Each data release contains the complete genomic sequences for all viral pathogens and related strains that are available for species in the above-named families. In addition to sequence data, the VBRC provides a curation for each virus species, resulting in a searchable, comprehensive mini-review of gene function relating genotype to biological phenotype, with special emphasis on pathogenesis.

Proper citation: VBRC (RRID:SCR_005971) Copy   

•   Source: SciCrunch Registry

http://www.hcvdb.org/

The Hepatitis C Virus Database (HCVdb) is a cooperative project of several groups with the mission of providing to the scientific community studying the hepatitis C virus a comprehensive battery of informational and analytical tools. The Viral Bioinformatics Resource Center (VBRC), the Immune Epitope Database and Analysis Resource (IEDB), the Broad Institute Microbial Sequencing Center (MSC), and the Los Alamos HCV Sequence Database (HCV-LANL) are combining forces to acquire and annotate data on Hepatitis C virus, and to develop and utilize new tools to facilitate the study of this group of organisms.

Proper citation: Hepatitis C Virus Database (HCVdb) (RRID:SCR_005718) Copy   

•   Source: SciCrunch Registry

http://www.ctotstudies.org

Project portal for a cooperative research program to improve short and long-term graft and patient survival. CTOT is an investigative consortium for conducting clinical and associated mechanistic studies that will lead to improved outcomes for transplant recipients.

Proper citation: Clinical Trials in Organ Transplantation (CTOT) (RRID:SCR_015859) Copy   

•   Source: SciCrunch Registry

http://www.ctotc.org

Project portal for a cooperative research program sponsored by the National Institute of Allergy and Infectious Diseases (NIAID). CTOT-C is an investigative consortium for conducting clinical and associated mechanistic studies that will lead to improved outcomes for pediatric heart, lung, or kidney transplant recipients.

Proper citation: Clinical Trials in Organ Transplantation in Children (CTOT-C) (RRID:SCR_015860) Copy   

•   Source: SciCrunch Registry

https://metadatacenter.org

Develops information technologies that make authoring complete metadata more manageable. Its products aim to facilitate using the metadata in further research.Center to improve metadata and its use throughout biomedical sciences. Develops information technologies that make authoring complete metadata more manageable through better interfaces, terminology, metadata practices, and analytics. Optimizes metadata pathway from provider to end user. Provides way for funders to specify what metadata they want to collect as part of research life cycle.

Proper citation: Center for Expanded Data Annotation and Retrieval (RRID:SCR_016269) Copy   

•   Source: SciCrunch Registry

http://www.niaid.nih.gov/topics/alps/Pages/default.aspx

A disease-related portal about Autoimmune Lymphoproliferative Syndrome (ALPS) including research in the following categories: Medical and Genetic Description, Database of Mutations, Database of ALPS-FAS Mutations, and Molecular Pathways. Autoimmune Lymphoproliferative Syndrome (ALPS) is a recently recognized disease in which a genetic defect in programmed cell death, or apoptosis, leads to breakdown of lymphocyte homeostasis and normal immunologic tolerance. It is an inherited disorder of the immune system that affects both children and adults. In ALPS, unusually high numbers of white blood cells called lymphocytes accumulate in the lymph nodes, liver, and spleen, which can lead to enlargement of these organs. Database of Mutations * All existing ALPS-FAS mutations (NIH Web site) * ALPS-FAS * ALPS Type Ia (most common type) ** Reported FAS (TNFRSF6) mutations causing ALPS ** Distribution of FAS (TNFRSF6) mutations ** FAS (TNFRSF6) polymorphisms * ALPS Type II

Proper citation: Autoimmune Lymphoproliferative Syndrome Information (RRID:SCR_006451) Copy   

•   Source: SciCrunch Registry

http://www.autoimmunitycenters.org/

Nine centers that conduct clinical trials and basic research on new immune-based therapies for autoimmune diseases. This program enhances interactions between scientists and clinicians in order to accelerate the translation of research findings into medical applications. By promoting better coordination and communication, and enabling limited resources to be pooled, ACEs is one of NIAID''''s primary vehicles for both expanding our knowledge and improving our ability to effectively prevent and treat autoimmune diseases. This coordinated approach incorporates key recommendations of the NIH Autoimmune Diseases Research Plan and will ensure progress in identifying new and highly effective therapies for autoimmune diseases. ACEs is advancing the search for effective treatments through: * Diverse Autoimmunity Expertise Medical researchers at ACEs include rheumatologists, neurologists, gastroenterologists, and endocrinologists who are among the elite in their respective fields. * Strong Mechanistic Foundation ACEs augment each clinical trial with extensive basic studies designed to enhance understanding of the mechanisms responsible for tolerance initiation, maintenance, or loss, including the role of cytokines, regulatory T cells, and accessory cells, to name a few. * Streamlined Patient Recruitment The cooperative nature of ACEs helps scientists recruit patients from distinct geographical areas. The rigorous clinical and basic science approach of ACEs helps maintain a high level of treatment and analysis, enabling informative comparisons between patient groups.

Proper citation: Autoimmunity Centers of Excellence (RRID:SCR_006510) Copy   

•   Source: SciCrunch Registry

https://www.fludb.org/brc/home.spg?decorator=influenza

The Influenza Research Database (IRD) serves as a public repository and analysis platform for flu sequence, experiment, surveillance and related data.

Proper citation: Influenza Research Database (IRD) (RRID:SCR_006641) Copy   

•   Source: SciCrunch Registry

https://pave.niaid.nih.gov

Collection of curated papillomavirus genomic sequences, accompanied by web-based sequence analysis tools. Database and web applications support the storage, annotation, analysis, and exchange of information.

Proper citation: PaVE (RRID:SCR_016599) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.niaid.nih.gov/hasp

Web server to visualize phylogenetic, biochemical, and immunological hemagglutinin data in the three-dimensional context of homology models. Database and structural visualization platform for comparative models of influenza A hemagglutinin proteins.

Proper citation: HASP (RRID:SCR_016615) Copy   

•   Source: SciCrunch Registry

https://github.com/dpeerlab/phenograph

Software tool as clustering method designed for high dimensional single cell data. Algorithmically defines phenotypes in high dimensional single cell data. Used for large scale analysis of single cell heterogeneity.

Proper citation: Phenograph (RRID:SCR_016919) Copy   

•   Source: SciCrunch Registry

https://csgid.org/csgid/metal_sites

Metal binding site validation server. Used for systematic inspection of the metal-binding architectures in macromolecular structures. The validation parameters that CMM examines cover the entire binding environment of the metal ion, including the position, charge and type of atoms and residues surrounding the metal.

Proper citation: CheckMyMetal (RRID:SCR_016887) Copy   

•   Source: SciCrunch Registry

https://immunedb.readthedocs.io/en/latest/

Software system for storing and analyzing high throughput B and T cell immune receptor sequencing data. Comprised of web interface and of Python analysis tools to process raw reads for gene usage, infer clones, aggregate data, and run downstream analyses, or in conjunction with other AIRR tools using its import and export features.

Proper citation: ImmuneDB (RRID:SCR_017125) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://vdjserver.org/

A web application immune repertoire management, analysis, and archiving. Users can collaborate and share data either privately or publicly. Users can perform a variety of tasks, such as create and share projects with other users, conduct pre-processing tasks on single end reads, run IgBlast, and obtain basic repertoire characterization results for B cell receptor and T cell receptor repertoires.

Proper citation: VDJ Server (RRID:SCR_014356) Copy   

•   Source: SciCrunch Registry

http://rast.nmpdr.org

A SEED-quality automated service that annotates complete or nearly complete bacterial and archaeal genomes across the entire phylogenetic tree. RAST can also be used to analyze draft genomes.

Proper citation: RAST Server (RRID:SCR_014606) Copy   

•   Source: SciCrunch Registry