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https://github.com/taborlab/FlowCal

Open source software tool for automatically converting flow cytometry data from arbitrary to calibrated units. Can be run using intuitive Microsoft Excel interface, or customizable Python scripts. Software accepts Flow Cytometry Standard (FCS) files as inputs and is compatible with different calibration particles, fluorescent probes, and cell types. Automatically gates data, calculates common statistics, and produces plots.

Proper citation: FlowCal (RRID:SCR_018140) Copy   

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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   

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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.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://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   

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http://hcv.lanl.gov/content/immuno/immuno-main.html

The HCV Immunology Database contains a curated inventory of immunological epitopes in HCV and their interaction with the immune system, with associated retrieval and analysis tools. The funding for the HCV database project has stopped, and this website and the HCV immunology database are no longer maintained. The site will stay up, but problems will not be fixed. The database was last updated in September 2007. The HIV immunology website contains the same tools, and may be usable for non-HCV-specific analyses. For new epitope information, users of this database can try the Immuno Epitope Database (http://www.immuneepitope.org).

Proper citation: HCV Immunology Database (RRID:SCR_007086) Copy   

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http://www.nmpdr.org/FIG/wiki/view.cgi

The National Microbial Pathogen Data Resource provides curated annotations in an environment for comparative analysis of genomes and biological subsystems, with an emphasis on the food-borne pathogens Campylobacter, Listeria, Staphylococcus, Streptococcus, and Vibrio; as well as the STD pathogens Chlamydiaceae, Haemophilus, Mycoplasma, Neisseria, Treponema, and Ureaplasma. This edition of the NMPDR includes 47 archaeal, 725 bacterial, and 29 eukaryal genomes with 3,257,100 genetic features, of which 1,338,895 are in FIGfams curated using 616 active subsystems. ''''''Notice to NMPDR Users'''''' - The NMPDR BRC contract ended in December 2009. At that time we ceased maintenance of the NMPDR web resource and data. Bacterial data from NMPDR has been transferred to PATRIC (http://www.patricbrc.org), a new consolidated BRC for all NIAID category A-C priority pathogenic bacteria. NMPDR was a collaboration among researchers from the Computation Institute of the University of Chicago, the Fellowship for Interpretation of Genomes (FIG), Argonne National Laboratory, and the National Center for Supercomputing Applications (NCSA) at the University of Illinois.

Proper citation: NMPDR (RRID:SCR_007821) Copy   

•   Source: SciCrunch Registry

http://patricbrc.vbi.vt.edu/portal/portal/patric/IncumbentBRCs?page=eric

ERIC is a resource of annotated enterobacterial genomes. Information is available and accessed through a open web portal uniting biological data and analysis tools. ERIC contains information on Escherichia, Shigella, Salmonella, Yersinia, and other microorgansims. ERIC has recently been moved over to PATRIC: The PATRIC BRC is now responsible for all bacterial species in the NIAID Category A-C Priority Pathogen lists for biodefense research, and pathogens causing emerging/reemerging infectious diseases. For ERIC users, we understand that the resource was valuable to your work. As such, we will be doing our very best to create a useful PATRIC resource to continue supporting your work. We realize that the transition will cause disruptions. However, it is a priority for us to work with established BRC users and communities to identify and prioritize our transition efforts. We have concentrated on the transfer of genomic data for this initial release. We anticipate adding new data, tools, and website features over the next several months. We look forward to working with you during the next 5 years., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ERIC (RRID:SCR_007644) Copy   

•   Source: SciCrunch Registry

http://pathema.jcvi.org/Pathema/index.html

Pathema is one of the eight Bioinformatics Resource Centers designed to serve as a core resource for the bio-defense and infectious disease research community. Pathema strives to support basic research and accelerate scientific progress for understanding, detecting, diagnosing and treating an established set of six target NIAID Category A-C pathogens: Category A priority pathogens; Bacillus anthracis and Clostridium botulinum, and Category B priority pathogens; Burkholderia mallei, Burkholderia pseudomallei, Clostridium perfringens and Entamoeba histolytica. Each target pathogen is represented in one of four distinct clade-specific Pathema web resources and underlying databases developed to target the specific data and analysis needs of each scientific community. All publicly available complete genome projects of phylogenetically related organisms are also represented, providing a comprehensive collection of organisms for comparative analyses. Pathema facilitates the scientific exploration of genomic and related data through its integration with web-based analysis tools, customized to obtain, display, and compute results relevant to ongoing pathogen research. Pathema serves the bio-defense and infectious disease research community by disseminating data resulting from pathogen genome sequencing projects and providing access to the results of inter-genomic comparisons for these organisms. The Pathema BRC contract ends in December 2009. At that time JCVI will cease maintenance of the Pathema web resource and data. The PATRIC team, located at the Virginia Bioinformatics Institute, created and maintains a consolidated BRC for all of the NIAID category A-C priority pathogenic bacteria. The EuPathDB team at the University of Pennsylvania will support all eukaryotic pathogens. Pathema transferred all data and software to PATRIC and EuPathDB for incorporation into their new Web-based bioinformatics resource.

Proper citation: Pathema (RRID:SCR_010585) Copy   

•   Source: SciCrunch Registry

http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

•   Source: SciCrunch Registry

http://www-sequence.stanford.edu/group/candida/

The Stanford Genome Technology Center began a whole genome shotgun sequencing of strain SC5314 of Candida albicans. After reaching its original goal of 1.5X mean coverage of the haploid genome (16Mb) in summer, 1998, Stanford was awarded a supplemental grant to continue sequencing up to a coverage of 10X, performing as much assembly of the sequence as possible, using recognizable genes as nucleation points. Candida albicans is one of the most commonly encountered human pathogens, causing a wide variety of infections ranging from mucosal infections in generally healthy persons to life-threatening systemic infections in individuals with impaired immunity. Oral and esophogeal Candida infections are frequently seen in AIDS patients. Few classes of drugs are effective against these fungal infections, and all of them have limitations with regard to efficacy and side-effects.

Proper citation: Sequencing of Candida Albicans (RRID:SCR_013437) Copy   

•   Source: SciCrunch Registry

http://PlasmoDB.org

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

Proper citation: PlasmoDB (RRID:SCR_013331) Copy   

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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

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   

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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   

•   Source: SciCrunch Registry

http://tools.dice-database.org/GOnet/)

Web tool for interactive Gene Ontology analysis of any biological data sources resulting in gene or protein lists.

Proper citation: GOnet (RRID:SCR_018977) 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.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   

•   Source: SciCrunch Registry