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https://github.com/BioDepot/BioDepot-workflow-builder
Software tool to create and execute reproducible bioinformatics workflows using drag and drop interface. Graphical widgets represent Docker containers executing modular task. Widgets are linked graphically to build bioinformatics workflows that can be reproducibly deployed across different local and cloud platforms. Each widget contains form-based user interface to facilitate parameter entry and console to display intermediate results.
Proper citation: BioDepot-workflow-builder (RRID:SCR_017402) Copy
https://www.rdocumentation.org/packages/DGCA/versions/1.0.2
Software R package to perform differential gene correlation analysis. Performs differential correlation analysis on input matrices, with multiple conditions specified by design matrix.
Proper citation: Differential Gene Correlation Analysis (RRID:SCR_020964) Copy
https://cran.r-project.org/web/packages/celltrackR/index.html
Software R package to analyze immune cell migration data. Supports pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration.Available measures include displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, steps, or subtracks with varying length.
Proper citation: celltrackR (RRID:SCR_021021) Copy
https://github.com/Cai-Lab-at-University-of-Michigan/nTracer
Software tool as plug-in for ImageJ software. Used for tracing microscopic images.
Proper citation: nTracer (RRID:SCR_023032) Copy
https://rdrr.io/cran/DrInsight/src/R/drug.identification.R
Software connectivity mapping based drug repurposing tool that identifies drugs that can potentially reverse query disease phenotype or have similar functions with query drugs.
Proper citation: DrInsight (RRID:SCR_023871) 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.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
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
https://cedar.metadatacenter.org/
Web application for creating, collecting, testing, and sharing metadata. It provides templates for metadata models or structures, and is capable of testing those models quickly using real data.
Proper citation: CEDAR Workbench (RRID:SCR_016270) Copy
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
https://software.broadinstitute.org/software/discovar/blog/
Software tool for variant calling with reference and de novo assembly of genomes. The heart of DISCOVAR is a de novo genome assembler which can generate de novo assemblies for both large and small genomes.
Proper citation: Discovar assembler (RRID:SCR_016755) Copy
http://research.mssm.edu/integrative-network-biology/Software.html
Software tool as probabilistic multi omics data matching procedure to curate data, identify and correct data annotation and errors in large databases. Used to check potential labeling errors in profiles where number of cis relationships is small, such as miRNA and RPPA profiles.
Proper citation: proMODMatcher (RRID:SCR_017219) Copy
https://github.com/epistasislab/hibachi
Software tool that creates data sets with particular characteristics. Method and open source software for simulating complex biological and biomedical data to aid in comparing and evaluating machine learning methods.
Proper citation: Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (RRID:SCR_017140) Copy
http://hcv.lanl.gov/content/sequence/HCV/ToolsOutline.html
The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. This central website provides annotated sequences and analysis tools that will be helpful to HCV scientists worldwide. Things you can do: * Find sequences in the database * Download sequences from the database * Retrieve data about the sequences * Analyze sequences * Work with the sequences using our tools * Download ready-made alignments The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of approximately 280 visits per day from distinct IP addresses.
Proper citation: HCV Sequence Database (RRID:SCR_006019) Copy
Web-based linked data server and browser specifically designed for ontology terms, it supports ontology visualization, query, and development. Ontobee provides a web interface for displaying the details and hierarchy of a specific ontology term. Meanwhile, Ontobee provides a RDF source code for the particular web page, which supports remote query of the ontology term and the Semantic Web. Ontobee provides an efficient and publicly available method to promote ontology sharing, interoperability, and data integration.
Proper citation: Ontobee (RRID:SCR_006321) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
Proper citation: DAVID (RRID:SCR_001881) Copy
EuPathDB integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises veterinary and medically important parasitic protozoa including human pathogenic species of genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as database but unifies access to three major existing individual organism databases, PlasmoDB.org, ToxoDB.org and CryptoDB.org, and integrates these databases with data available from additional sources. Through ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases. EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with eukaryotic pathogens.
Proper citation: Eukaryotic Pathogen Database Resources (RRID:SCR_004512) Copy
Research consortium to advance scientific research in the primary immune deficiency diseases (PIDD) and: * Assemble and maintain a registry of patients with primary immunodeficiency diseases to provide a minimum estimate of the prevalence of each disorder in the United States. Provide a comprehensive clinical picture of each disorder and act as a resource for clinical and laboratory research. * Establish a multifaceted mentoring program to introduce new investigators into the field and stimulate interest and research in primary immune deficiency diseases. * Establish an advisory/review committee to maintain a cell/DNA Repository of biologic material from well-characterized PIDD patients for the advancement of scientific research USIDNET operates a large database of patient information for your use. The purpose and scope of this project is to assemble and maintain a registry of residents with primary immunodeficiency diseases. The project was started with the Registry of U.S. Residents with Chronic Granulomatous Disease. Since then, the registry has been expanded and now collects data on all primary immunodeficiency disorders. The following are just a few of the diseases housed in the registry: Chronic Granulomatous Disease, Common Variable Immunodeficiency Disease, DiGeorge Anomaly, Hyper IgM Syndrome, Leukocyte Adhesion Defect, Severe Combined Immunodeficiency Disease, Wiskott-Aldrich Syndrome, X-Linked Agammaglobulinemia Physicians who would like to register their patients or access the registry are encouraged to contact Onika Davis or Lamar Hamilton, USIDNET team, at odavis (at) primaryimmune.org, or lhamilton (at) primaryimmune.org
Proper citation: USIDNET: US Immunodeficiency Network (RRID:SCR_004672) Copy
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/
Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) 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
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