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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.
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
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
Resource to aggregate all outbreak information into single location during outbreaks of emerging diseases, such as COVID-19.
Proper citation: outbreak.info (RRID:SCR_018282) Copy
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
Software R package for mathematical modeling of infectious disease over networks. Provides tools for simulating and analyzing mathematical models of infectious disease dynamics. Mathematical Modeling of Infectious Disease Dynamics.
Proper citation: EpiModel (RRID:SCR_018539) Copy
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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