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http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

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http://ontodog.hegroup.org/index.php

Ontodog is a web-based ontology view generator. It can generate inSubset annotation ontology, user preferred label annotation ontology and subset of source ontology. Simply provide Ontodog input term file (Microsoft Excel file or tab-delimited text file), select one source ontology or enter your own source ontology and SPARQL endpoint, then set the settings for Ontodog output files and get the OWL (RDF/XML) Output files. Ontodog performs the basic ontology modularization-like function, i.e.,it automatically extracts all axioms and related terms associated with user-specified signature term(s). In addition, Ontodog includes extra features: (1) extracting all instance data associated with the retrieved class terms and annotations; and (2) recursively extracting all axioms and related terms indirectly associated with signature terms. More features are being added to Ontodog, such as relabeling preferred names for various ontology terms to fit in with the needs from a specific community. The Ontodog input data requires a source ontology and a list of user-specified signature terms in tab-delimited format. Ontodog provides the template files for generating the signature terms as the input terms file to download. There are several output options that the users can choose based on their needs. With more and more ontologies being developed, Ontodog offers a timely web-based package of solutions for ontology view generation. Ontodog provides an efficient approach to promote ontology sharing and interoperability. It is easy to use and does not require knowledge of SPARQL, script programming, and command line operation. Ontodog is developed to serve the ontology community for ontology reuse. It is freely available under the Apache License 2.0. The source code is made available under Apache License 2.0.

Proper citation: Ontodog: A Web-based Ontology View Generator (RRID:SCR_005061) Copy   

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http://www.nsrrc.missouri.edu/

Provides access to critically needed swine models of human health and disease as well as a central resource for reagents, creation of new genetically modified swine, and information and training related to use of swine models in biomedical research.

Proper citation: National Swine Resource and Research Center (RRID:SCR_006855) Copy   

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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   

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http://metagenomics.anl.gov/

An automated analysis platform for metagenomes providing quantitative insights into microbial populations based on sequence data. The server primarily provides upload, quality control, automated annotation and analysis for prokaryotic metagenomic shotgun samples.

Proper citation: MG-RAST (RRID:SCR_004814) Copy   

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http://crcview.hegroup.org/

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   

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http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&type=1

Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible

Proper citation: EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) Copy   

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https://www.immunespace.org/

A consortium of university groups to characterize human immune populations. The Human Immunology Project Consortium (HIPC) program, established in 2010 by the NIAID Division of Allergy, Immunology, and Transplantation, is a major collaborative effort that is generating large amounts of cross-center and cross-assay data including high-dimensional data to characterize the status of the immune system in diverse populations under both normal conditions and in response to stimuli. This large data problem has given birth to ImmuneSpace, a powerful data management and analysis engine where datasets can be easily explored and analyzed using state-of-the-art computational tools.

Proper citation: ImmuneSpace (RRID:SCR_010508) Copy   

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https://github.com/JCVenterInstitute/NSForest/releases

Software tool as method that takes cluster results from single cell nuclei RNAseq experiments and generates lists of minimal markers needed to define each cell type cluster. Utilizes random forest of decision trees machine learning approach. Used to determine minimum set of marker genes whose combined expression identified cells of given type with maximum classification accuracy.

Proper citation: NS-Forest (RRID:SCR_018348) Copy   

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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   

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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   

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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   

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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   

•   Source: SciCrunch Registry

https://mibig.secondarymetabolites.org/

MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters.

Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy   

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http://www.hiv.lanl.gov/content/index

Contains comprehensive data on HIV genetic sequences and immunological epitopes. This collection of databases contains tools to visualize and analyze HIV-related data.

Proper citation: HIV Databases (RRID:SCR_000614) Copy   

•   Source: SciCrunch Registry

http://www.immuneprofiling.org/

Consortium established to capitalize on recent advances in immune profiling methods in order to create a novel public resource that characterizes diverse states of the human immune system following infection; prior to and following vaccination against an infectious disease; or prior to and following treatment with an immune adjuvant that targets a known innate immune receptor(s). Through this program, well-characterized human cohorts are studied using a variety of modern analytic tools, including multiplex transcriptional, cytokine, and proteomic assays; multiparameter phenotyping of leukocyte subsets; assessment of leukocyte functional status; and multiple computational methods. Centralized research resources and a comprehensive, centralized database will be constructed for use by the greater scientific community. The information gained from the program will provide a comprehensive understanding of the human immune system and its regulation, and will reveal novel associations between components of the immune system and other biological systems, identify novel immune mediators and pathways, establish predictors of vaccine safety in different populations, and enable the rapid evaluation of different vaccine formulations and administration regimens in human populations.

Proper citation: Human Immunology Project Consortium (RRID:SCR_001491) Copy   

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https://david.ncifcrf.gov/

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   

•   Source: SciCrunch Registry

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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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   

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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   

•   Source: SciCrunch Registry