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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   

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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   

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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://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   

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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   

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http://hcv.lanl.gov/

The Hepatitis C Virus (HCV) Database Project strives to present HCV-associated genetic and immunologic data in a user-friendly way, by providing access to the central database via web-accessible search interfaces and supplying a number of analysis tools.

Proper citation: HCV Databases (RRID:SCR_002863) 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

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://pypi.org/project/pmlb/

Python wrapper for Penn Machine Learning Benchmark data repository. Large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. Part of PyPI https://pypi.org/

Proper citation: Penn machine learning benchmark repository (RRID:SCR_017138) Copy   

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https://med.nyu.edu/research/scientific-cores-shared-resources/ion-laboratory

Electrophysiology core facility that is part of Ion Channels and Transporters in Immunity Research Program.Research area includes ion channel and transporter function and ionic signaling in immune cells.Users who are studying other cell types or organ systems are welcome.Provides assistance with experimental design, training, implementation, and data analysis.

Proper citation: New York University School of Medicine IonLab Core Facility (RRID:SCR_021754) Copy   

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https://github.com/ScilifelabDataCentre/node-pathogens-portal

Software package and code for Pathogen Portal node (i.e. a local Pathogens Portal, such as the Swedish and Dutch Pathogens Portals). Allows users to create their own node quickly and easily.

Proper citation: Pathogens Portal Node Toolbox (RRID:SCR_027086) Copy   

•   Source: SciCrunch Registry

https://curie.utmb.edu/prosurf.html

Web server for predicting interacting sites on protein surfaces. Analyzes solvent-accessible residues likely to participate in PPIs.Predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of protein complex.

Proper citation: InterProSurf (RRID:SCR_027791) Copy   

•   Source: SciCrunch Registry

http://www.genome.ou.edu/cneo.html

Cryptococcus neoformans is an encapsulated yeast that infects the human host via the respiratory tract where it usually causes an inapparent infection. In the susceptible host, it may disseminate, typically producing a chronic and life-threatening meningitis. The Cryptococcus neoformans serotypes A and D are responsible for the overwhelming majority of pulmonary infections in AIDS patients. Cryptococcus neoformans strain H99 Latest Data Release - May 19, 2004 To date, we have isolated ca. 3750 cDNA clones from Cryptococcus neoformans strain H99 in collaboration with Drs. Juneann Murphy and Dave Dyer at the University of Oklahoma Health Sciences Center''s Department of Microbiology and Immunology in Oklahoma City and Kent Buchanan at the Tulane University Medical School, New Orleans, LA. The Cryptococcus neoformans strain H99 EST''s have been generated by Doris Kupfer, Heather Bell, Sunkyoung So, Yuong Tang, and Jennifer Lewis at the University of Oklahoma''s Advanced Center for Genome Technology, in the Department of Chemistry and Biochemistry. We now have end sequenced all available templates (ca. 7500 reactions) from both ends of the directionally cloned inserts after excision into pBlueScript SK-. . All of our data is available from our ftp site, and we now have added the ability to perform blast searches on this data. A keyword search of a blastx search of GenBank with this data also is available but we have not yet linked this to a unigene database as the number of EST''s sequenced doesn''t warrent this yet.

Proper citation: Cryptococcus Neoformans cDNA Sequencing (RRID:SCR_008462) Copy   

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http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/apidots/

Note: ApiDots is currently unavailable. For data on apicomplexan EST assemblies, please see EuPathDB ApiDots is a database integrating mRNA/EST sequences from numerous Apicomplexan parasites. ESTs and mRNAs were clustered and further assembled to generate consensus sequences. These consensus sequences were then subjected to database searches against protein sequences and protein domain sequences. The underlying relational structure of this database allows researchers to analyze these data and pose biologically interesting questions.

Proper citation: ApiDots (RRID:SCR_001778) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/immunology/index

An annotated, searchable collection of HIV-1 cytotoxic and helper T-cell epitopes and antibody binding sites, plus related tools and information. The goal of this database is to provide a comprehensive listing of defined HIV epitopes. These data are also printed in the HIV Molecular Immunology compendium, which is updated yearly and provided free of charge to scientific researchers, both by online download and as a printed copy. The data included in this database are extracted from the HIV immunology literature. HIV-specific B-cell and T-cell responses are summarized and annotated. Immunological responses are divided into three sections, CTL (CD8+), T helper (CD4+), and antibody. Within these sections, defined epitopes are organized by protein and binding sites within each protein, moving from left to right through the coding regions spanning the HIV genome. We include human responses to natural HIV infections, as well as vaccine studies in a range of animal models and human trials. Responses that are not specifically defined, such as responses to whole proteins or monoclonal antibody responses to discontinuous epitopes, are summarized at the end of each protein sub-section. Studies describing general HIV responses to the virus, but not to any specific protein, are included at the end of each section. The annotation includes information such as cross-reactivity, escape mutations, antibody sequence, TCR usage, functional domains that overlap with an epitope, immune response associations with rates of progression and therapy, and how specific epitopes were experimentally defined. Basic information such as HLA specificities for T-cell epitopes, isotypes of monoclonal antibodies, and epitope sequences are included whenever possible. All studies that we can find that incorporate the use of a specific monoclonal antibody are included in the entry for that antibody. A single T-cell epitope can have multiple entries, generally one entry per study. Finally, tables and maps of all defined linear epitopes relative to the HXB2 reference proteins are provided. Alignments of CTL, helper T-cell, and antibody epitopes are available through the search interfaces. Only responses to HIV-1 and HIV-2 are included in the database.

Proper citation: HIV Molecular Immunology Database (RRID:SCR_002893) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/vaccine/home.html

An overview of HIV and SIV vaccine trials and their outcomes. It was developed as a tool for compilation, search and comparison of published studies on SIV, HIV and SHIV vaccine trials in nonhuman primates. We used a set of criteria to scan Pubmed for relevant studies to enter into the database. In selecting studies for entry, priority was given to recently published studies in journals generally regarded as the primary source of information pertaining to HIV and SIV vaccine research in nonhuman primates. In most cases, we give priority to challenge studies, where the animals received a live virus to measure the "efficacy" of the immunogen(s) inoculated during the course of the investigation. The HIV Sequence Database focuses on five primary goals: *Collecting HIV and SIV sequence data (all sequences since 1987) *Curating and annotating this data, and making it available to the scientific community *Computer analysis of HIV and related sequences *Production of software for the analysis of (sequence) data *Publication of the data and analyses on this site and in a yearly printed publication, the HIV sequence Compendium, which is available free of charge

Proper citation: Nonhuman Primate HIV/SIV Vaccine Trials Database (RRID:SCR_002274) Copy   

•   Source: SciCrunch Registry