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http://lussierlab.org/GO-Module/GOModule.cgi

GO-Module provides an interface to reduce the dimensionality of GO enrichment results and produce interpretable biomodules of significant GO terms organized by hierarchical knowledge that contain only true positive results. Users can download a text file of GO terms annotated with their significance and identified biomodules, a network visualization of resultant GO IDs or terms in PDF format, and view results in an online table. Platform: Online tool

Proper citation: GO-Module (RRID:SCR_005813) Copy   

•   Source: SciCrunch Registry

http://dunham.gs.washington.edu/protocols.shtml

A portal for Maitreya Dunham's lab, which works on the genomic analysis of experimental evolution in yeast using microarrays and the chemostat. Research interests of the lab include experimental evolution of genetic networks in yeast, aneuploidy and copy number variation, comparative genomics, technology development and human genetics in yeast.

Proper citation: Maitreya Dunham's Lab (RRID:SCR_000784) Copy   

•   Source: SciCrunch Registry

https://catalog.coriell.org/

A biorepository and biomaterial supply resource which establishes, verifies, maintains, and distributes cells, cultures and DNA derived from cell cultures to the scientific community around the world. Scientists can browse the sample catalog and request specific cell lines for their research studies. An inventory of the remaining stock of each cell line and DNA preparation is presented in real time. Coriell's significant cell biobank collections include: NIGMS Human Genetic Cell Repository, NINDS Human Genetics DNA and Cell Line Repository, NIA Aging Cell Repository, NHGRI Sample Repository for Human Genetic Research, NEI Age-Related Eye Disease Study (AREDS) Genetic Repository, HD Community BioRepository, American Diabetes Association, GENNID Study, and Autism Research Resource. The repositories are ISO 9000-2001 compliant.

Proper citation: Coriell Cell Repositories (RRID:SCR_003244) Copy   

•   Source: SciCrunch Registry

http://datalad.org/

Project to adapt model of open source software distributions to address technical limitations of data sharing and develop all components of data distribution. Builds on top of git-annex and extends it with intuitive command line interface. Enables users to operate on data using familiar concepts, such as files and directories, while transparently managing data access and authorization with underlying hosting providers. Can create DataLad datasets using any data files published on the web.

Proper citation: DataLad (RRID:SCR_003931) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/dbSTS/

THIS RESOURCE IS NO LONGER IN SERVICE, as of October 1, 2013; however, the site is still accessible. NCBI resource that contains sequence and mapping data on short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. The dbSTS database offers a route for submission of STS sequences to GenBank. It is designed especially for the submission of large batches of STS sequences.

Proper citation: dbSTS (RRID:SCR_000400) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://www.ndriresource.org/

NDRI is a Not-For-Profit (501c3) Corporation dedicated to providing the highest quality human biomaterials for research. NDRI makes it easy for researchers to get the human tissues and organs they need, prepared, preserved and shipped precisely according to their specific scientific protocols, as quickly as possible, and in the largest available quantities. NDRI provides researchers with protocol specific human neurological tissues such as brain stem, spinal cord, and basal ganglia, among others. In addition to control specimens, NDRI recovers tissues from donors with a variety of diseases, including Down syndrome, Parkinsons disease, Alzheimers disease, schizophrenia, and dementia. Through the NDRI 24/7 referral and procurement system, research consented biospecimens can be provided from low post mortem interval donors preserved at 4ºC, frozen or snap frozen, fixed, paraffin embedded, or as unstained slides.

Proper citation: National Disease Research Interchange (RRID:SCR_000550) Copy   

•   Source: SciCrunch Registry

http://wikipathways.org/

Open and collaborative platform dedicated to curation of biological pathways. Each pathway has dedicated wiki page, displaying current diagram, description, references, download options, version history, and component gene and protein lists. Database of biological pathways maintained by and for scientific community.

Proper citation: WikiPathways (RRID:SCR_002134) Copy   

•   Source: SciCrunch Registry

http://magi.cs.brown.edu/

A tool for annotating, exploring, and analyzing gene sets that may be associated with cancer.

Proper citation: Mutation Annotation and Genomic Interpretation (RRID:SCR_002800) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

http://ndbserver.rutgers.edu/

A database of three-dimensional structural information about nucleic acids and their complexes. In addition to primary data, it contains derived geometric data, classifications of structures and motifs, standards for describing nucleic acid features, as well as tools and software for the analysis of nucleic acids. A variety of search capabilities are available, as are many different types of reports. NDB maintains the macromolecular Crystallographic Information File (mmCIF).

Proper citation: Nucleic Acid Database (RRID:SCR_003255) Copy   

•   Source: SciCrunch Registry

http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

•   Source: SciCrunch Registry

http://mistdb.com

Database which contains the signal transduction proteins for complete and draft bacterial and archaeal genomes. The MiST2 database identifies and catalogs the repertoire of signal transduction proteins in microbial genomes.

Proper citation: MiST - Microbial Signal Transduction database (RRID:SCR_003166) Copy   

•   Source: SciCrunch Registry

https://www.jax.org/news-and-insights/2013/february/komp2-mice-phenotyping-and-availability

Knockout Mouse Phenotyping Project, JAX information about their contributions to KOMP2 project. Project to generate and phenotype single gene KO mouse strains from KOMP ES cell lines. Strains are phenotyped using protocols in pipeline designed by International Mouse Phenotyping Consortium. There are three NIH-funded phenotyping centers in United States: JAX, BaSH Consortium (Baylor College of Medicine, the Wellcome Trust Sanger Institute and MRC Harwell), and the DTCC Consortium (University of California at Davis, the Toronto Center for Phenogenomics, Children’s Hospital Oakland Research Institute (CHORI) and Charles River ).

Proper citation: KOMP2 (RRID:SCR_017528) Copy   

•   Source: SciCrunch Registry

https://scienceofbehaviorchange.org/about/

Repository for behavioral science measures that have been validated or are in process of being validated in accordance with SOBC Experimental Medicine Approach.

Proper citation: Science of Behavior Change Research Network (RRID:SCR_017385) Copy   

•   Source: SciCrunch Registry

https://www.portal.brain-bican.org/

Provides molecular and anatomical foundational framework for study of brain function and disorders.Comprehensive Center on Human and Non-Human Primate Brain Cell Atlases with goal to build reference brain cell atlases that will be used throughout research community.

Proper citation: BRAIN Initiative Cell Atlas Network (RRID:SCR_022794) Copy   

•   Source: SciCrunch Registry

http://www.lamhdi.org/

THIS RESOURCE IS NO LONGER IN SERVICE, it has been replaced by Monarch Initiative. LAMHDI, the initiative to Link Animal Models to Human DIsease, is designed to accelerate the research process by providing biomedical researchers with a simple, comprehensive Web-based resource to find the best animal model for their research. LAMDHI is a free, Web-based, resource to help researchers bridge the gap between bench testing and human trials. It provides a free, unbiased resource that enables scientists to quickly find the best animal models for their research studies. LAMHDI includes mouse data from MGI, the Mouse Genome Informatics website; zebrafish data from ZFIN, the Zebrafish Model Organism Database; rat data from RGD, the Rat Genome Database; yeast data from SGD, the Saccharomyces Genome Database; and fly data from FlyBase. LAMHDI.org is operational today, and data is added regularly. Enhancements are planned to let researchers contribute their knowledge of the animal models available through LAMHDI. The LAMHDI goal is to allow researchers to share information about and access to animal models so they can refine research and testing, and reduce or replace the use of animal models where possible. LAMHDI Database Search: LAMHDI brings together scientifically validated information from various sources to create a composite multi-species database of animal models of human disease. To do this, the LAMHDI database is prepared from a variety of sources. The LAMHDI team takes publicly available data from OMIM, NCBI''s Entrez Gene database, Homologene, and WikiPathways, and builds a mathematical graph (think of it as a map or a web) that links these data together. OMIM is used to link human diseases with specific human genes, and Entrez provides universal identifiers for each of those genes. Human genes are linked to their counterpart genes in other species with Homologene, and those genes are linked to other genes tentatively or authoritatively using the data in WikiPathways. This preparatory work gives LAMHDI a web of human diseases linked to specific human genes, orthologous human genes, homologous genes in other species, and both human and non-human genes involved in specific metabolic pathways associated with those diseases. LAMHDI includes model data that partners provide directly from their data structures. For instance, MGI provides information about mouse models, including a disease for each model, as well as some genetic information (the ID of the model, in fact, identifies one or more genes). ZFIN provides genetic information for each zebrafish model, but no diseases, so zebrafish models are integrated by using the genes as the glue. For instance, a zebrafish model built to feature the zebrafish PKD2 gene would plug into the larger disease-gene map at the node representing the zebrafish PKD2 gene, which is connected to the node representing the human PKD2 gene, which in turn is connected to the node representing the human disease known as polycystic kidney disease. (Some of the partner data LAMHDI receives can even extend the base map. MGI provides a disease for every model, and in some cases this allows the creation of a disease-to-gene relationship in the LAMHDI database that might not already be documented in the OMIM dataset.) With curatorial and model information in hand, LAMHDI runs a lengthy automated process that exhaustively searches for every possible path between each model and each disease in the data, up to a set number of hops, producing for each disease-to-model pair a set of links from the disease to the model. The algorithm avoids circular paths and paths that include more than one disease anywhere in the middle of the path. At the end of this phase, LAMHDI has a comprehensive set of paths representing all the disease-to-model relationships in the data, varying in length from one hop to many hops. Each disease-to-model path is essentially a string of nodes in the data, where each node represents a disease, a gene, a linkage between genes (an orthologue, a homologue, or a pathway connection, referred to as a gene cluster or association), or a model. Each node has a human-friendly label, a set of terms and keywords, and - in most cases - a URL linking the node to the data source where it originated. When a researcher submits a search on the LAMHDI website, LAMHDI searches for the user''s search terms in its precomputed list of all known disease-to-model paths. It looks for the terms not only in the disease and model nodes, but also in every node along each path. The complete set of hits may include multiple paths between any given disease-to-model pair of endpoints. Each of these disease-to-model pair sets is ordered by the number of hops it involves, and the one involving the fewest hops is chosen to represent its respective disease-to-model pair in the search results presented to the user. Results are sorted by scores that represent their matches. The number of hops is one barometer of the strength of the evidence linking the model and the disease; fewer hops indicates the relationship is stronger, more hops indicates it may be weaker. This indicator works best for comparing models from a single partner dataset: MGI explicitly identifies a disease for each mouse model, so there can be disease-to-model hits for mice that involve just one hop. Because ZFIN does not explicitly identify a disease for each model, no zebrafish model will involve fewer than four hops to the nearest disease, from the zebrafish model to a zebrafish gene to a gene cluster to a human gene to a human disease.

Proper citation: LAMHDI: The Initiative to Link Animal Models to Human DIsease (RRID:SCR_008643) Copy   

•   Source: SciCrunch Registry

https://www.tycho.pitt.edu/

Database to advance the availability and use of public health data for science and policy making that includes data from all weekly notifiable disease reports for the United States dating back to 1888. Additional U.S. and international data will be released twice yearly.

Proper citation: Project Tycho (RRID:SCR_010489) Copy   

•   Source: SciCrunch Registry

https://github.com/sqjin/CellChat

Software R toolkit for inference, visualization and analysis of cell-cell communication from single cell data.Quantitatively infers and analyzes intercellular communication networks from single-cell RNA-sequencing data. Predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Classifies signaling pathways and delineates conserved and context specific pathways across different datasets.

Proper citation: CellChat (RRID:SCR_021946) Copy   

•   Source: SciCrunch Registry

http://www2.bsc.gwu.edu/bsc/oneproj.php?pkey=28

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Collect, store, and distribute genetic samples from cases and controls of type 1 diabetes and diabetic nephropathy for investigator-driven research into the genetic basis of diabetic nephropathy. As the risk of kidney complications in type 1 diabetes appears to have a considerable genetic component, this study assembled a large data resource for researchers attempting to identify causative genetic variants. The types of data collected allowed traditional case-control testing, a rapid and often powerful approach, and family-based analysis, a robust approach that is not influenced by population substructure.

Proper citation: Genetics of Kidneys in Diabetes (RRID:SCR_000133) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/custom/library/digital-collections/projectionmap

Data set of thalamo-centric mesoscopic projection maps to the cortex and striatum. The maps are established through two-color, viral (rAAV)-based tracing images and high throughout imaging.

Proper citation: Mouse Thalamic Projectome Dataset (RRID:SCR_015702) Copy   

•   Source: SciCrunch Registry