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http://www.sci.utah.edu/cibc-research/highlights/24-research-highlights/cibc-highlights/221-scirun-biopse.html

A simulation software package which hosts a collection of algorithms used to run bioelectric field simulations inside of SCIRun. The software provided in the package may be used for geometric modeling, simulation, and visualization for solving bioelectric field problems.

Proper citation: BioPSE (RRID:SCR_014044) 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   

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http://disco.neuinfo.org

DISCO is an information integration approach designed to facilitate interoperation among Internet resources. It consists of a set of tools and services that allows resource providers who maintain information to share it with automated systems such as NIF. NIF is then able to harvest the information and keep those sets of information up-to-date. How is this accomplished? By using a series of files and/or scripts which are then placed in the root directory of the resource developer''s resource. (NIF can also host the files on its servers and crawl for changes there.) Once the files of the resource providers are in place, and DISCO is notified, the DISCO server can then recognize and consume the information shared, providing machine understandable information to NIF Integrator Servers (also known as Aggregators) about your resource. What can DISCO do for my resource? * Inform search engines about your resource and keep your NIF Registry resource description up-to-date. * Expose your data (semi-structured datasets or fields within your structured database) through NIF''s Data Federation you choose what data will be shared. * Create links from an NCBI database (e.g., PubMed, Protein, Nucleotide, etc.) to your data records in NIF using Entrez LinkOut. * Advertise your terminology or ontological information. * Share your resource''s news with the NIF community., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DISCO (RRID:SCR_004586) Copy   

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http://xgc.nci.nih.gov/

NIH initiative to support production of cDNA libraries, clones and 5'/3' sequences and to provide set of full-length (open reading frame) sequences and cDNA clones of expressed genes for Xenopus laevis and Xenopus tropicalis. Clones distribution is outsourced to for profit companies. Project concluded in September 2008. Resources generated by XGC are publicly accessible to biomedical research community. All sequences are deposited into GenBank.Corresponding clones are available through IMAGE clone distribution network. With conclusion of XGC project, GenBank records of XGC sequences will be frozen, without further updates. Since knowledge of what constitutes full-length coding region for some of genes and transcripts for which we have XGC clones will likely change in future, users planning to order XGC clones will need to monitor for these changes. Users can make use of genome browsers and gene-specific databases, such as UCSC Genome browser, NCBI's Map Viewer, and Entrez Gene, to view relevant regions of genome (browsers) or gene-related information (Entrez Gene).

Proper citation: Xenopus Gene Collection (RRID:SCR_007023) Copy   

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http://www.sanger.ac.uk/Projects/D_rerio/zmp/

Create knockout alleles in protein coding genes in the zebrafish genome, using a combination of whole exome enrichment and Illumina next generation sequencing, with the aim to cover them all. Each allele created is analyzed for morphological differences and published on the ZMP site. Transcript counting is performed on alleles with a morphological phenotype. Alleles generated are archived and can be requested from this site through the Zebrafish International Resource Center (ZIRC). You may register to receive updates on genes of interest, or browse a complete list, or search by Ensembl ID, gene name or human and mouse orthologue.

Proper citation: ZMP (RRID:SCR_006161) Copy   

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http://www.physionet.org/physiobank/database/gaitpdb/

Database that contains measures of gait from 93 patients with idiopathic PD (mean age: 66.3 years; 63% men), and 73 healthy controls (mean age: 66.3 years; 55% men). The database includes the vertical ground reaction force records of subjects as they walked at their usual, self-selected pace for approximately 2 minutes on level ground. Underneath each foot were 8 sensors (Ultraflex Computer Dyno Graphy, Infotronic Inc.) that measure force (in Newtons) as a function of time. The output of each of these 16 sensors has been digitized and recorded at 100 samples per second, and the records also include two signals that reflect the sum of the 8 sensor outputs for each foot. This database also includes demographic information, measures of disease severity (i.e., using the Hoehn & Yahr staging and/or the Unified Parkinson's Disease Rating Scale) and other related measures (available in HTML or xls spreadsheet format). A subset of the database includes measures recorded as subjects performed a second task (serial 7 subtractions) while walking, which shows excerpts of swing time series from a patient with PD and a control subject, under usual walking conditions and when performing serial 7 subtractions. Under usual walking conditions, variability is larger in the patient with PD (Coefficient of Variation = 2.7%), compared to the control subject (CV = 1.3%). Variability increases during dual tasking in the subject with PD (CV = 6.5%), but not in the control subject (CV = 1.2%).

Proper citation: Gait in Parkinson's Disease (RRID:SCR_006891) Copy   

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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   

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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   

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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   

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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   

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http://integromedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.

Proper citation: IntegromeDB (RRID:SCR_004620) Copy   

•   Source: SciCrunch Registry
  

http://www.phenologs.org/

Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided.

Proper citation: Phenologs (RRID:SCR_005529) Copy   

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http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry
  

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   

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http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry
  

http://tulane.edu/som/regenmed/services/index.cfm

The Stem Cell Research and Regenerative Medicine''s Tissue Culture Core provides cells for research use within the department, as well as for distribution to other facilities. The core obtains hMSCs from bone marrow donor samples and expands these cells for research use. The hMSC''s are also characterized for bone, fat and cartilage differentiation, and are stored on site for use. The Tissue Culture Core also handles the expansion and characterization of mouse and rat MSC''s. The animal cells are cultured in a separate area, and never interact with human derived cells. We also have a supply of hMSC''s marked with GFP+, Mito Red and Mito Blue available.

Proper citation: Tulane Stem Cell Research and Regenerative Medicine Tissue Culture Core (RRID:SCR_007342) Copy   

•   Source: SciCrunch Registry
  

http://www.nhpreagents.org

Center that facilitates the optimal use of nonhuman primate models in biomedical research by identifying, developing, characterizing and producing reagents for monitoring or modulating immune responses. They distribute non-human primate-specific antibodies for in vitro diagnostics, as well as develop and produce primate recombinant antibodies for in vivo cell depletion or modulating immune responses.

Proper citation: Nonhuman Primate Reagent Resource (RRID:SCR_012986) Copy   

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http://www.ncbcs.org/

The NCBCs are a set of networked computation core facilities for biomedical infrastructure funded under the NIH Common Fund, the National Program of Excellence in Biomedical Computing (NPEBC). There are seven funded Centers that cover systems biology, image processing, biophysical modeling, biomedical ontologies, information integration, and tools for gene-phenotype and disease analysis. The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease. Each Center has Cores that are focused on (1) computational science, (2) biomedical computational science and (3) driving biological projects whose intent is to drive the interaction between computational and biomedical computational science. In addition to the Centers, the NIH has a number of active program announcements to develop collaborations with the biomedical research community��this includes announcements from the Biomedical Information Science and Technology Initiative (BISTI) and the Program for Collaborations with National Centers for Biomedical Computing. There are numerous efforts in education and training that emanate from the Centers and there is an annual all hands meeting.

Proper citation: National Centers for Biomedical Computing (RRID:SCR_010635) Copy   

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https://www.ebi.ac.uk/intact/complex/#annotations:fIzBXhJPEeej78Pl6R0ScA

Database and encyclopaedic resource of macromolecular complexes found in key model organisms from scientific literature. Data includes protein-only complexes, protein-small molecules, and protein-nucleic acid complexes. The information within the portal is manually curated and available for download.

Proper citation: Complex Portal (RRID:SCR_015038) Copy   

•   Source: SciCrunch Registry