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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
https://github.com/sreeramkannan/Shannon
Software tool for de novo transcriptome assembly from RNA-Seq data.
Proper citation: Shannon (RRID:SCR_017037) Copy
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
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
https://github.com/ANGSD/ngsRelate
Software tool for estimating pairwise relatedness from next-generation sequencing data.
Proper citation: ngsRelate (RRID:SCR_016588) Copy
https://bioconductor.org/packages/release/bioc/html/ComplexHeatmap.html
Software package to arrange multiple heatmaps and support various annotation graphics. Used to visualize associations between different sources of data sets and to reveal potential patterns.
Proper citation: ComplexHeatmap (RRID:SCR_017270) Copy
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
Platform for individuals who want to make their own data available for research. Used by people to join network with others who wish to contribute to vital research in partnership with and alongside leading scientists. Personal tool for saving and displaying medical information.
Proper citation: Hugo Data (RRID:SCR_022763) Copy
https://cumulus.readthedocs.io/en/stable
Software tool as cloud based single cell genomics and spatial transcriptomics data analysis framework that is scalable to massive amounts of data and able to process variety of data types. Consists of cloud analysis workflow, Python analysis package and visualization application. Supports analysis of single-cell RNA-seq, CITE-seq, Perturb-seq, single-cell ATAC-seq, single-cell immune repertoire and spatial transcriptomics data.
Proper citation: Cumulus (RRID:SCR_021644) Copy
https://sourceforge.net/p/iris-scanning/calliope
Software package for image processing for MATLAB. Used for processing of calcium imaging data.
Proper citation: Calliope calcium imaging processing package (RRID:SCR_021213) Copy
Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.
Proper citation: OpenNeuro (RRID:SCR_005031) Copy
Ratings or validation data are available for this resource
Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy
http://mialab.mrn.org/index.html
MIALAB, headed by Dr. Vince Calhoun, focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data. Much of our time is spent working on new methods for flexible analysis of brain imaging data. The use of data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. To this end, we draw heavily from the areas of image processing, adaptive signal processing, estimation theory, neural networks, statistical signal processing, and pattern recognition.
Proper citation: MIALAB - Medical Image Analysis Lab (RRID:SCR_006089) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A public resource for sharing general proteomics information including data (Tranche repository), tools, and news. Joining or creating a group/project provides tools and standards for collaboration, project management, data annotation, permissions, permanent storage, and publication.
Proper citation: Proteome Commons (RRID:SCR_006234) Copy
http://www.cbrc.jp/htbin/show_tffactor_mw
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 13, 2016.
A dataset about transcriptional regulation in eukaryotic cells, including data such as transcription factors and their binding sites and profiles. Resource is in Chinese.
Proper citation: TFFACTOR (RRID:SCR_000519) Copy
http://www.rand.org/labor/FLS/MHSS.html
A data set of the health and socioeconomic factors that affect the elderly in Matlab, a region of rural Bangladesh. The survey captures measurements and statistics such as adult survival, health status, health care utilization, resource flows between generations and the impact of community services and infrastructure on adult health care. Data was collected through surveys that touch on four topics: household and individual information; determinants of natural fertility; migration out of the community; and community and provider survey of healthcare and education infrastructure.
Proper citation: Matlab Health and Socio-Economic Survey (RRID:SCR_008942) Copy
http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.
Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy
http://locustdb.genomics.org.cn/
The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects. Its transcriptomic data provide invaluable information for molecular entomology study of the insect and pave a way for comparative studies of other medically, agronomically, and ecologically relevant insects. This first transcriptomic database of the locust (LocustDB) has been developed, building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. It currently hosts 45,474 high quality EST sequences from the locust, which were assembled into 12,161 unigenes. This database contains original sequence data, including homologous/orthologous sequences, functional annotations, pathway analysis, and codon usage, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. LocustDB also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. It starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporation of in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.
Proper citation: Migratory Locust EST Database (RRID:SCR_008201) Copy
http://amazonia.montp.inserm.fr/
A web interface and associated tools for easy query of public human transcriptome data by keyword, through thematic pages with list annotations. Amazonia provides a thematic entry to public transcriptomes: users may for instance query a gene on a Stem Cells page, where they will see the expression of their favorite gene across selected microarray experiments related to stem cell biology. This selection of samples can be customized at will among the 6331 samples currently present in the database. Every transcriptome study results in the identification of lists of genes relevant to a given biological condition. In order to include this valuable information in any new query in the Amazonia database, they indicate for each gene in which lists it is included. This is a straightforward and efficient way to synthesize hundreds of microarray publications., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: AmaZonia: Explore the Jungle of Microarrays Results (RRID:SCR_008405) Copy
http://www.molecularbrain.org/
MolecularBrain is an attempt to collect, collates, analyze and present the microarray derived gene expression data from various brain regions side by side. Transcription Profile of any gene in Mouse (online) and Human Brain (not yet) can be accessed as a histogram along with links to access various aspects of that gene. The expression levels were calculated from microarray data deposited at GEO (Gene expression omnibus). The molecular brain database could be searched using the built in search tool with the terms Entrez GeneID, gene symbol, synonym or description. Gene information along with their expression values can be also accessed from the alphabetical list of gene symbols on the footer. The protocol and GEO sample information is available.
Proper citation: Molecular Brain: Transcription Profiles of Mouse and Human Brains (RRID:SCR_008689) Copy
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