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http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

•   Source: SciCrunch Registry

http://www.gensat.org/

Gene expression data and maps of mouse central nervous system. Gene expression atlas of developing adult central nervous system in mouse, using in situ hybridization and transgenic mouse techniques. Collection of pictorial gene expression maps of brain and spinal cord of mouse. Provides tools to catalog, map, and electrophysiologically record individual cells. Application of Cre recombinase technologies allows for cell-specific gene manipulation. Transgenic mice created by this project are available to scientific community.

Proper citation: Gene Expression Nervous System Atlas (RRID:SCR_002721) Copy   

•   Source: SciCrunch Registry

http://www.nihclinicalcollection.com

A plated array of approximately 450 small molecules that have a history of use in human clinical trials. The collection was assembled by the National Institutes of Health (NIH) through the Molecular Libraries Roadmap Initiative as part of its mission to enable the use of compound screens in biomedical research. Similar collections of FDA approved drugs have proven to be rich sources of undiscovered bioactivity and therapeutic potential. The clinically tested compounds in the NCC are highly drug-like with known safety profiles. These compounds can provide excellent starting points for medicinal chemistry optimization and, for high-affinity targets, may even be appropriate for direct human use in new disease areas.

Proper citation: NIH Clinical Collection (RRID:SCR_007349) Copy   

•   Source: SciCrunch Registry

http://www.project-redcap.org/

Web application that allows users to build and manage online surveys and databases. Using REDCap's stream-lined process for rapidly developing projects, you may create and design projects using 1) the online method from your web browser using the Online Designer; and/or 2) the offline method by constructing a "data dictionary" template file in Microsoft Excel, which can be later uploaded into REDCap. Both surveys and databases (or a mixture of the two) can be built using these methods. REDCap provides audit trails for tracking data manipulation and user activity, as well as automated export procedures for seamless data downloads to Excel, PDF, and common statistical packages (SPSS, SAS, Stata, R). Also included are a built-in project calendar, a scheduling module, ad hoc reporting tools, and advanced features, such as branching logic, file uploading, and calculated fields. REDCap has a quick and easy software installation process, so that you can get REDCap running and fully functional in a matter of minutes. Several language translations have already been compiled for REDCap (e.g. Chinese, French, German, Portuguese), and it is anticipated that other languages will be available in full versions of REDCap soon. The REDCap Shared Library is a repository for REDCap data collection instruments and forms that can be downloaded and used by researchers at REDCap partner institutions.

Proper citation: REDCap (RRID:SCR_003445) Copy   

•   Source: SciCrunch Registry

https://github.com/immunogenomics/harmony

Software R package to project cells into shared embedding in which cells group by cell type rather than dataset specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. Used for integration of single cell data.

Proper citation: Harmony (RRID:SCR_022206) Copy   

•   Source: SciCrunch Registry

https://bioinformaticshome.com/tools/rna-seq/descriptions/LIGER.html

Software R package for integrating and analyzing multiple single-cell datasets. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors. Used for analysis of multiple scRNA-seq data sets.

Proper citation: LIGER (RRID:SCR_018100) Copy   

•   Source: SciCrunch Registry

https://www.teamtat.org

Web based collaborative text annotation tool. Used for managing multi-user, multi-label document annotation. Project managers can specify annotation schema for entities and relations and select annotators and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. Displays figures from full text.

Proper citation: TeamTat (RRID:SCR_023439) Copy   

•   Source: SciCrunch Registry

http://provean.jcvi.org/

A software tool which predicts whether an amino acid substitution or indel has an impact on the biological function of a protein.

Proper citation: PROVEAN (RRID:SCR_002182) Copy   

•   Source: SciCrunch Registry

http://tvmouse.compmed.ucdavis.edu/

Educational resource to introduce users to the anatomy, physiology, histology, and pathology of the laboratory mouse, with an emphasis on the Genetically Engineered Mouse (GEM). It provides access to histological images, scanned at high resolution and browsable through Zoomify, movie loops and animations derived from MRI, correlated MRI and histology. It has CNS data but is focused on the whole body, e.g., physiological data is available for the heart in the form of wave patterns, histology, CNS, pathology, magnetic resonance imaging, neoplasms; animation, virtual histology, mouse, correlated imaging, necropsy, whole mouse. It may be useful to neuroscientists by relating brain anatomy to the rest of the body. There is a movie illustrating necropsy of the mouse. A link to a compendium of histological slices of brain neoplasms is provided under the Image Archive link. There is a CNS link under construction for anatomical system, which presumably will include detailed CT imaging. This site still appears to be under construction.

Proper citation: Visible Mouse Project (RRID:SCR_002393) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/

Registry and results database of federally and privately supported clinical trials conducted in United States and around world. Provides information about purpose of trial, who may participate, locations, and phone numbers for more details. This information should be used in conjunction with advice from health care professionals.Offers information for locating federally and privately supported clinical trials for wide range of diseases and conditions. Research study in human volunteers to answer specific health questions. Interventional trials determine whether experimental treatments or new ways of using known therapies are safe and effective under controlled environments. Observational trials address health issues in large groups of people or populations in natural settings. ClinicalTrials.gov contains trials sponsored by National Institutes of Health, other federal agencies, and private industry. Studies listed in database are conducted in all 50 States and in 178 countries.

Proper citation: ClinicalTrials.gov (RRID:SCR_002309) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/software/eegift/index.html

Implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) EEG data. This MATLAB toolbox is compatible with MATLAB 6.5 and higher.

Proper citation: Group ICA Of EEG Toolbox (RRID:SCR_002478) Copy   

•   Source: SciCrunch Registry

http://www.cmhd.ca/genetrap/

Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) Copy   

•   Source: SciCrunch Registry

https://simtk.org

A National NIH Center for Biomedical Computing that focuses on physics-based simulation of biological structures and provides open access to high quality simulation tools, accurate models and the people behind them. It serves as a repository for models that are published (as well as the associated code) to create a living archive of simulation scholarship. Simtk.org is organized into projects. A project represents a research endeavor, a software package or a collection of documents and publications. Includes sharing of image files, media, references to publications and manuscripts, as well as executables and applications for download and source code. Simulation tools are free to download and space is available for developers to manage, share and disseminate code.

Proper citation: Simtk.org (RRID:SCR_002680) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/foldvillin

An archive of hundreds of all-atom, explicit solvent molecular dynamics simulations that were performed on a set of nine unfolded conformations of a variant of the villin headpiece subdomain (HP-35 NleNle). It includes scripts for accessing the archive of villin trajectories as well as a VMD plug-in for viewing the trajectories. In addition, all starting structures used in the trajectories are also provided. The simulations were generated using a distributed computing method utilizing the symmetric multiprocessing paradigm for individual nodes of the Folding_at_home distributed computing network. The villin trajectories in the archive are divided into two projects: PROJ3036 and PROJ3037. PROJ3036 contains trajectories starting from nine non-folded configurations. PROJ3037 contains trajectories starting from the native (folded) state. Runs 0 through 8 (in PROJ3036) correspond to starting configurations 0 through 8 discussed in the paper in J. Mol. Biol. (2007) 374(3):806-816 (see the publications tab for a full reference), whereas RUN9 uses the same starting configuration as RUN8. Each run contains 100 trajectories (named clone 0-99), each with the same starting configuration but different random velocities. Trajectories vary in their length of time and are subdivided into frames, also known as a generation. Each frame contains around 400 configurational snapshots, or timepoints, of the trajectory, with the last configurational snapshot of frame i corresponding to the first configurational snapshot of generation i+1. The goal is to allow researchers to analyze and benefit from the many trajectories produced through the simulations.

Proper citation: Molecular Simulation Trajectories Archive of a Villin Variant (RRID:SCR_002704) Copy   

•   Source: SciCrunch Registry

http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

•   Source: SciCrunch Registry

http://www.compucell3d.org/

Open-source simulation environment for multi-cell, single-cell-based modeling of tissues, organs and organisms. It uses Cellular Potts Model to model cell behavior.

Proper citation: CompuCell3D (RRID:SCR_003052) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://ccdb.ucsd.edu/SAO

Ontology that describes structures from the dimensional range encompassing cellular and subcellular structure, supracellular domains, and macromolecules. It is built according to ontology development best practices (re-use of existing ontologies; formal definitions of terms; use of foundational ontologies). It describes the parts of neurons and glia and how these parts come together to define supracellular structures such as synapses and neuropil. Molecular specializations of each compartment and cell type are identified. The SAO was designed with the goal of providing a means to annotate cellular and subcellular data obtained from light and electron microscopy, including assigning macromolecules to their appropriate subcellular domains. The SAO thus provides a bridge between ontologies that describe molecular species and those concerned with more gross anatomical scales. Because it is intended to integrate into ontological efforts at these other scales, particular care was taken to construct the ontology in a way that supports such integration.

Proper citation: Subcellular Anatomy Ontology (RRID:SCR_003486) Copy   

•   Source: SciCrunch Registry

https://bioportal.bioontology.org/ontologies/NEMO/?p=summary

Ontology that describes classes of event-related brain potentials (ERP) and their properties, including spatial, temporal, and functional (cognitive / behavioral) attributes, and data-level attributes (acquisition and analysis parameters). Its aim is to support data sharing, logic-based queries and mapping/integration of patterns across data from different labs, experiment paradigms, and modalities (EEG/MEG).

Proper citation: NEMO Ontology (RRID:SCR_003386) Copy   

•   Source: SciCrunch Registry