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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.
https://niaid.github.io/spice/
Software application for data mining and visualization. Used for analyzes of large FLOWJO data sets from polychromatic flow cytometry and organizing the normalized data graphically.
Proper citation: SPICE (RRID:SCR_016603) Copy
Web-based suite of phylogenetic analysis tools for use in evolutionary biology. Web application for comparative analysis of sequence alignments using statistical models. Used for analyzing evolutionary signatures in sequence data. Datamonkey 2.0 provides curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application.
Proper citation: Datamonkey (RRID:SCR_010278) Copy
http://purl.bioontology.org/ontology/IMMDIS
Ontology generated as part of the Bioinformatics Integration Support Contract (BISC) that is based on the National Library of Medicine (NLM) Medical Subject Headings; National Cancer Institute Thesaurus; International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM); ICD-10; and other open source public databases. Specific information may be available about a class, including Preferred_Name, DEFINITION, Synonym, etc.
Proper citation: Immune Disorder Ontology (RRID:SCR_010344) Copy
http://www.nitrc.org/projects/ap_seg_2013_nih/
A MATLAB GUI for segmenting and quantifying PET images with multi-focal and diffuse uptakes. It imports a PET image and allows the user to draw region of interests (ROIs) in 2D or 3D to roughly separate the object of interest from the background. The areas are then segmented using a PET image segmentation method based on Affinity Propagation clustering to cluster the image intensities into meaningful groups. For quantification, the Standardized Uptake Value measurements of the binary or the user defined ROI are SUVmax, SUVmean, and Volume (mm^3) and can be exported into an excel sheet.
Proper citation: NIH-CIDI Segmentation of PET Images based on Affinity Propagation Clustering (RRID:SCR_014151) Copy
Software R package for processing and analyzing single-cell ATAC-seq data. Used for integrative single cell chromatin accessibility analysis.Provides intuitive, user focused interface for complex single cell analysis, including doublet removal, single cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing.
Proper citation: ArchR (RRID:SCR_020982) Copy
https://bioweb.pasteur.fr/packages/pack@[email protected]
Open source software tool for analysing trace files generated by Bayesian MCMC runs. Software package for visualising and analysing MCMC trace files generated through Bayesian phylogenetic inference. Provides kernel density estimation, multivariate visualisation, demographic trajectory reconstruction, conditional posterior distribution summary and more.
Proper citation: Tracer (RRID:SCR_019121) Copy
https://github.com/datatagsuite
Software suite to enable discoverability of datasets. Enables submission of metadata on datasets to DataMed. Has core set of elements, which are generic and applicable to any type of dataset, and extended set that can accommodate more specialized data types. Platform independent model developed by NIH BD2K bioCADDIE project for DataMed Data Discovery Index prototype being developed. Also available as annotated serialization in schema.org, which in turn is widely used by major search engines like Google, Microsoft, Yahoo and Yandex.
Proper citation: DatA Tag Suite (RRID:SCR_019236) Copy
http://mummer.sourceforge.net/
Software package as system for rapidly aligning entire genomes. Alignment tool for DNA and protein sequences. Can align incomplete genomes.
Proper citation: MUMmer (RRID:SCR_018171) Copy
http://www.cbs.dtu.dk/services/NetMHCpan/
Web server for quantitative prediction of peptide binding to any MHC molecule of known sequence using artificial neural networks. Characterizes binding specificity of given major histocompatibility complex molecule and predicts peptide length profile and peptide binding affinity. NetMHCpan 3.0 is improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length data sets. NetMHCpan 4.0 is trained on naturally eluted ligands and on peptide binding affinity data. NetMHCpan-4.1 server predicts binding of peptides to any MHC molecule of known sequence using artificial neural networks (ANNs).
Proper citation: NetMHCpan Server (RRID:SCR_018182) Copy
http://web.cbio.uct.ac.za/~darren/rdp.html
Software package to analyse nucleotide sequence data and identify evidence of genetic recombination. RDP3 is version of RDP program for characterizing recombination events in DNA-sequence alignments. RDP4 is version of RDP program for detection and analysis of recombination patterns in virus genomes.
Proper citation: Recombination Detection Program (RRID:SCR_018537) Copy
Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.
Proper citation: CRCView (RRID:SCR_007092) 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
An integrated genomic and functional genomic database for the parasite Cryptosporidium. CryptoDB integrates whole genome sequence and annotation along with experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining. Organisms included in CryptoDB are Cryptosporidium parvum, Cryptosporidium hominis, Cryptosporidium muris and environmental isolate sequences from numerous species. CryptoDB is allied with the databases PlasmoDB and ToxoDB via ApiDB, an NIH/NIAID-funded Bioinformatics Resource Center. Tools include: * BLAST: Identify Sequence Similarities * Sequence Retrieval: Retrieve Specific Sequences using IDs and coordinates * PubMed and Entrez: View the Latest Cryptosporidium Pubmed and Entrez Results * Genome Browser: View Sequences and Features in the genome browser * CryptoCyc: Explore Automatically Defined Metabolic Pathways * Searches via Web Services: Web service access to our data
Proper citation: ApiDB CryptoDB (RRID:SCR_013455) Copy
http://immport.org/immport-open/public/reference/cytokineRegistry
A registry of cytokines, chemokines, and receptors generated for the purpose of collecting, integrating, and mapping between entity names and synonyms from several resources. These resources include MeSH, the Protein Ontology, EntrezGene, HGNC, MGI, UniProt and others.
Proper citation: Cytokine Registry (RRID:SCR_014368) Copy
http://imed.med.ucm.es/epimhc/
Database of naturally processed MHC-restricted peptide ligands and epitopes for customized computational vaccinology.
Proper citation: EPIMHC (RRID:SCR_016279) Copy
Collection of manually curated data regarding structure and antimicrobial activity of natural and synthetic peptides. Provides the information and analytical resources to develop antimicrobial compounds with the high therapeutic index.
Proper citation: Database of Antimicrobial Activity and Structure of Peptides (RRID:SCR_016600) Copy
Project combines immunology and computational biology laboratories in effort to establish complete road map of gene-expression and regulatory networks in all immune cells. Project will generate, with rigorously standardized conditions, complete compendium of genome-wide data sets showing expression of protein-coding genes for all defined cell populations of mouse immune system.
Proper citation: ImmGen (RRID:SCR_021792) Copy
http://www.niaid.nih.gov/about/organization/dait/pages/csgadp.aspx
Collaborative network of investigators with a focus on prevention of autoimmune disease, defined as halting the development of autoimmune disease prior to clinical onset by means other than global immunosuppression, and an emphasis on Type 1 diabetes. Its mission is to engage in scientific discovery that significantly advances knowledge for the prevention and regulation of autoimmune disease. The specific goals enunciated in pursuit of this mission are: * To create improved models of disease pathogenesis and therapy to better understand immune mechanisms that will provide opportunities for prevention strategies * To use these models as validation platforms with which to test new tools applicable to human studies * To encourage core expertise and collaborative projects designed for rapid translation from animal to human studies, emphasizing the development of surrogate markers for disease progression and/or regulation which can be utilized in the context of clinical trials
Proper citation: Cooperative Study Group for Autoimmune Disease Prevention (RRID:SCR_006803) Copy
http://www.nitrc.org/projects/dicomconvert/
A DICOM image converter based on the ITK IO mechanism for reading and writing images. The formats currently supported by the converter are DICOM to: Analyze (*.hdr); MetaImage (*.mhd); Nrrd (*.nhdr, *.nrrd).
Proper citation: DICOMConvert (RRID:SCR_014100) Copy
https://cibersort.stanford.edu/
Software tool to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data. Used for characterizing cell composition of complex tissues from their gene expression profiles, large scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets.
Proper citation: CIBERSORT (RRID:SCR_016955) Copy
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