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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.immunexpresso.org

Software tool as text-mining engine that structures and standardizes knowledge of immune intercellular communication. Knowledgebase contains interactions and separate mentions of cells or cytokines in context of thousands of diseases. Intercellular interactions were text-mined from all available PubMed abstracts across disease conditions.

Proper citation: immuneXpresso (RRID:SCR_017578) Copy   

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https://dice-database.org

Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics. Collection of identified cis-eQTLs for 12,254 unique genes, which represent 61% of all protein-coding genes expressed in human cell types. Datasets to help reveal effects of disease risk associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

Proper citation: Database of Immune Cell Epigenomes (RRID:SCR_018259) 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   

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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   

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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://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   

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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   

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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   

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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   

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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   

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https://github.com/JLSteenwyk/ClipKIT

Software fast and flexible alignment trimming tool that keeps phylogenetically informative sites and removes others. Multiple sequence alignment-trimming algorithm for accurate phylogenomic inference.

Proper citation: ClipKIT (RRID:SCR_026411) 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   

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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   

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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.jcvi.org/charprotdb/index.cgi/home

The Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ��synonymous accessions��. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.

Proper citation: CharProtDB: Characterized Protein Database (RRID:SCR_005872) 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   

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https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   

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https://omics.pnl.gov/software/ms-gf

Software that performs peptide identification by scoring MS/MS spectra against peptides derived from a protein sequence database.

Proper citation: MS-GF+ (RRID:SCR_015646) Copy   

•   Source: SciCrunch Registry