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https://www.ncbi.nlm.nih.gov/sutils/pasc/viridty.cgi

Web tool for analysis of pairwise identity distribution within viral families. Used for virus sequence-based classification. Data in the system are updated every day to reflect changes in virus taxonomy and additions of new virus sequences to the public database.

Proper citation: PASC (RRID:SCR_016642) Copy   

•   Source: SciCrunch Registry

http://home.cc.umanitoba.ca/~frist/Bit/

BIT Core at University of Manitoba, Manitoba, Canada, provides bioinformatics services, resources and collaborations. Support for Genome assembly and annotation, Microarray and Transcriptomics, Systems Biology and Pathway analysis, Databases, Data pipelines, Bioinformatics software, Custom software and programming, Project Wikis, Lab group computer management.

Proper citation: University of Manitoba Department of Plant Science Bio Information Technologies Lab Core Facility (RRID:SCR_017177) Copy   

•   Source: SciCrunch Registry

https://omicc.niaid.nih.gov

Community based, biologist friendly web platform for creating and meta analyzing annotated gene expression data compendia., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMiCC (RRID:SCR_016604) Copy   

•   Source: SciCrunch Registry

https://github.com/wilkinsonlab/epigenomics_pipeline

Software tool as epigenomics analysis pipeline for analysis of ChIP-Seq and RNA-Seq data using Docker images containing Galaxy and Jupyter.

Proper citation: Epigenomics Workflow on Galaxy and Jupyter (RRID:SCR_017544) Copy   

•   Source: SciCrunch Registry

https://opticalmapping.info

Platform to provide tutorials and resources in experimental design and data analysis to researchers interested in using optical mapping data.

Proper citation: OpticalMapping.info (RRID:SCR_017146) Copy   

•   Source: SciCrunch Registry

http://www.imgt.org/HighV-QUEST/home.action

Next generation B and T cell sequence alignment and characterization online surface by IMGT. Web portal for immunoglobulin (IG) or antibody and T cell receptor (TR) analysis from NGS high throughput and deep sequencing.

Proper citation: IMGT HighV-QUEST (RRID:SCR_018196) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/factoextra/index.html

R package from CRAN to extract and visualize the results of multivariate data analysis.

Proper citation: factoextra (RRID:SCR_016692) Copy   

•   Source: SciCrunch Registry

https://github.com/neurostuff/NiMARE

Software Python package for coordinate and image based meta analysis of neuroimaging data.

Proper citation: NiMARE (RRID:SCR_017398) Copy   

•   Source: SciCrunch Registry

https://www.iconplc.com/innovation/nonmem/

Software tool for nonlinear mixed effects modelling. Used for population pharmacokinetic and pharmacodynamic analysis and to simulate data and to fit data. Used in the development of new drugs. NONMEM versions up through 6 are the property of the Regents of the University of California, San Francisco, but ICON Development Solutions has exclusive rights to license their use. NONMEM 7 up to the current version is the property of ICON Development Solutions.

Proper citation: NONMEM (RRID:SCR_016986) Copy   

•   Source: SciCrunch Registry

http://redrocksw.com/

Software tool for statistics and data visualization by Red Rock Software, Inc. Provides unparalleled chart selection, data analysis and graph customization capabilities.

Proper citation: Deltagraph (RRID:SCR_018084) Copy   

•   Source: SciCrunch Registry

https://satijalab.org/seurat/get_started.html

Software as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

Proper citation: Seurat (RRID:SCR_016341) Copy   

•   Source: SciCrunch Registry

http://gst.ornl.gov/

We are the Computational Biology and Bioinformatics Group of the Biosciences Division of Oak Ridge National Laboratory. We conduct genetics research and system development in genomic sequencing, computational genome analysis, and computational protein structure analysis. We provide bioinformatics and analytic services and resources to collaborators, predict prospective gene and protein models for analysis, provide user services for the general community, including computer-annotated genomes in Genome Channel. Our collaborators include the Joint Genome Institute, ORNL''s Computer Science and Mathematics Division, the Tennessee Mouse Genome Consortium, the Joint Institute for Biological Sciences, and ORNL''s Genome Science and Technology Graduate Program.

Proper citation: Computational Biology at ORNL (RRID:SCR_005710) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/expressionprofiler/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry

http://xldb.fc.ul.pt/biotools/rebil/ssm/

FuSSiMeG is being discontinued, may not be working properly. Please use our new tool ProteinOn. Functional Semantic Similarity Measure between Gene Products (FuSSiMeG) provides a functional similarity measure between two proteins using the semantic similarity between the GO terms annotated with the proteins. Platform: Online tool

Proper citation: FuSSiMeG: Functional Semantic Similarity Measure between Gene-Products (RRID:SCR_005738) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/l2n/upload/register.php

A web-based software system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system.

Proper citation: Lists2Networks (RRID:SCR_006323) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

https://biocodecommons.org/

Platform provides resources for genomic observations from collection to analysis and publication. Works with standards community to ensure clear vocabularies and useful ontologies for biological resources and related assets. Biocode Commons is also collaborating on development of Biological Collections Ontology, working to better integrate ontologies, vocabularies, and relevant standards that are related to BCO.

Proper citation: Biocode Commons (RRID:SCR_024553) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/DPARSF

A MATLAB toolbox forpipeline data analysis of resting-state fMRI that is based on Statistical Parametric Mapping (SPM) and a plug-in software within DPABI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF, degree centrality, voxel-mirrored homotopic connectivity (VMHC) results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest. DPARSF basic edition is very easy to use while DPARSF advanced edition (alias: DPARSFA) is much more flexible and powerful. DPARSFA can parallel the computation for each subject, and can be used to reorient images interactively or define regions of interest interactively. Users can skip or combine the processing steps in DPARSF advanced edition freely.

Proper citation: DPARSF (RRID:SCR_002372) Copy   

•   Source: SciCrunch Registry

http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry

https://www.upf.edu/web/ntsa/downloads/-/asset_publisher/xvT6E4pczrBw/content/2012-nonrandomness-nonlinear-dependence-and-nonstationarity-of-electroencephalographic-recordings-from-epilepsy-patients

THIS RESOURCE IS NO LONGER IN SERVICE, documented November 23, 2020; EEG data set, source code, and results from 7500 signal pairs from 5 epilepsy patients analyzed in the manuscript, Andrzejak RG, Schindler K, Rummel C. Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients. Phys. Rev. E, 86, 046206, 2012. All Matlab source codes are included in the file ASR_Sources_2012_10_16.zip. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control.

Proper citation: Bern-Barcelona EEG database (RRID:SCR_001582) Copy   

•   Source: SciCrunch Registry