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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Collection of dissemination and exchange recorded biomedical signals and open-source software for analyzing them. Provides facilities for cooperative analysis of data and evaluation of proposed new algorithm. Providies free electronic access to PhysioBank data and PhysioToolkit software. Offers service and training via on-line tutorials to assist users at entry and more advanced levels. In cooperation with annual Computing in Cardiology conference, PhysioNet hosts series of challenges, in which researchers and students address unsolved problems of clinical or basic scientific interest using data and software provided by PhysioNet. All data included in PhysioBank, and all software included in PhysioToolkit, are carefully reviewed. Researchers are further invited to contribute data and software for review and possible inclusion in PhysioBank and PhysioToolkit. Please review guidelines before submitting material.
Proper citation: PhysioNet (RRID:SCR_007345) Copy
https://www.mcgill.ca/bic/resources/omega
Open data repository fully dedicated to MEG data in raw and processed form. The archive also contains anatomical MRI volumes and demographic and questionnaire information. Organized and stored as the Brain Imaging Data Structure (BIDS) with the integration of multimodal electrophysiology data. Directly readable by data-analysis software with Brainstorm. OMEGA will continue to expand, with contributions from the scientific community.
Proper citation: Open MEG Archive (RRID:SCR_014930) Copy
http://www.atsdr.cdc.gov/toxprofiles
A database of information about contaminants found at hazardous waste sites. The toxicological profiles are cataloged by chemical with the NTIS order number.
Proper citation: CDC Toxprofiles (RRID:SCR_000900) Copy
Consortium represents all publicly available gene trap cell lines, which are available on non-collaborative basis for nominal handling fees. Researchers can search and browse IGTC database for cell lines of interest using accession numbers or IDs, keywords, sequence data, tissue expression profiles and biological pathways, can find trapped genes of interest on IGTC website, and order cell lines for generation of mutant mice through blastocyst injection. Consortium members include: BayGenomics (USA), Centre for Modelling Human Disease (Toronto, Canada), Embryonic Stem Cell Database (University of Manitoba, Canada), Exchangeable Gene Trap Clones (Kumamoto University, Japan), German Gene Trap Consortium provider (Germany), Sanger Institute Gene Trap Resource (Cambridge, UK), Soriano Lab Gene Trap Resource (Mount Sinai School of Medicine, New York, USA), Texas Institute for Genomic Medicine - TIGM (USA), TIGEM-IRBM Gene Trap (Naples, Italy).
Proper citation: International Gene Trap Consortium (RRID:SCR_002305) Copy
http://discover.nci.nih.gov/gominer/
GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.
Proper citation: GoMiner (RRID:SCR_002360) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 10th,2023. Commercial provider of cognitive assessments, including their proprietary database, the Brain Resource International Database (BRID) that allows users to quantify individual differences in brain function, compare individual performance against peers, and provide a robust frame of reference for clinical assessment and treatment decisions. Database provides evidence for brain behavior connection so important to reliably enabling optimal solutions for mental health and wellbeing. It powers all Brain Resource products.
Proper citation: Brain Resource (RRID:SCR_006172) Copy
http://www.ch.embnet.org/software/COILS_form.html
COILS is a program that compares a sequence to a database of known parallel two-stranded coiled-coils and derives a similarity score. By comparing this score to the distribution of scores in globular and coiled-coil proteins, the program then calculates the probability that the sequence will adopt a coiled-coil conformation.
Proper citation: COILS: Prediction of Coiled Coil Regions in Proteins (RRID:SCR_008440) Copy
https://www.broadinstitute.org/ccle/
A collaborative project between the Broad Institute and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation, with the goal of conducting a detailed genetic and pharmacologic characterization of a large panel of human cancer models. The CCLE also works to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
Proper citation: Cancer Cell Line Encyclopedia (RRID:SCR_013836) Copy
http://www.ini.uzh.ch/~acardona/trakem2.html
An ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation. Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database. What can you do with it? * Semantic segmentation editor: order segmentations in tree hierarchies, whose template is exportable for reuse in other, comparable projects. * Model, visualize and export 3D. * Work from your laptop on your huge, remote image storage. * Work with an endless number of images, limited only by the hard drive capacity. Dozens of formats supported thanks to LOCI Bioformats and ImageJ. * Import stacks and even entire grids (montages) of images, automatically stitch them together and homogenize their histograms for best montaging quality. * Add layers conveniently. A layer represents, for example, one 50 nm section (for TEM) or a confocal section. Each layer has its own Z coordinate and thickness, and contains images, labels, areas, nodes of 3d skeletons, profiles... * Insert layer sets into layers: so your electron microscopy serial sections can live inside your optical microscopy sections. * Run any ImageJ plugin on any image. * Measure everything: areas, volumes, pixel intensities, etc. using both built-in data structures and segmentation types, and standard ImageJ ROIs. And with double dissectors! * Visualize RGB color channels changing the opacity of each on the fly, non-destructively. * Annotate images non-destructively with floating text labels, which you can rotate/scale on the fly and display in any color. * Montage/register/stitch/blend images manually with transparencies, semiautomatically, or fully automatically within and across sections, with translation, rigid, similarity and affine models with automatically extracted SIFT features. * Correct the lens distortion present in the images, like those generated in transmission electron microscopy. * Add alpha masks to images using ROIs, for example to split images in two or more parts, or to remove the borders of an image or collection of images. * Model neuronal arbors with 3D skeletons (with areas or radiuses), and synapses with connectors. * Undo all steps. And much more...
Proper citation: TrakEM2 (RRID:SCR_008954) Copy
International biobank storing whole blood and DNA from 200,000 individuals, serum and plasma samples from more than 100,000 individuals as well as urine, RNA tubes, cells, buffy coat and Na-heparin tubes for environmental analysis for as many as 50,000 individuals. All bio-specimens from the HUNT surveys are collected, processed and stored at the HUNT Biobank in Levanger. The National CONOR Biobank is located on the same site, where it serves as a central research repository for DNA samples from all the largest Norwegian health surveys. These make up the Cohorts of Norway (CONOR), which include samples from more than 200,000 individuals. * HUNT 1 was carried out in 1984-1986 to establish the health history of 75,000 people. * HUNT 2, carried out in 1995-1997, focused on the evolution of the health history of 74,000 people. This included blood sample collection from 65,000 people. The data that accompany biospecimens in the biobank are stored in secured computer systems that run complex database management and analysis software. * HUNT 3 was completed in June 2008. 93,210 people were invited to participate in the study, and as of the 6th of June, 2008, 48,289 people participated (52% participation rate). The data, collected by means of questionnaires, interviews, clinical examinations and collection of blood and urine samples, will be ready for analysis in January 2009. * Young-HUNT is the adolescent part of HUNT including participants aged 13-19 years. Young-HUNT1 (1995-97) was conducted as part of HUNT2, 9141 adolescents participated (90% response rate). Young-HUNT2 (2000-01) was a follow-up study of Young-HUNT1, 2400 students participated in both studies (77% of the invited). Young-HUNT3 (2006-08) was a new cross-sectional study as part of HUNT3. This time 8677 adolescents participated (87% response rate). Data collection included self-reported questionnaires, structured interviews, clinical measurements and, in Young-HUNT3, buccal smears. All institutions with research expertise can apply for access to analyze HUNT data. Projects must have recommendations from The Regional Committee for Medical Research in Norway (REK) and be registered with The Norwegian Social Science Data Services (NSD).
Proper citation: Hunt Biobank (RRID:SCR_010626) Copy
The official compendium for the Anatomical Therapeutic Chemical Classification System (ATC)-code descriptions. The Centre's main tasks are development and maintenance of the ATC/DDD system, including: * To classify drugs according to the ATC system. * Priority will be given to the classification of single substances, while combination products available internationally (i.e. important fixed combinations) will be dealt with as far as possible. * To establish DDDs for drugs which have been assigned an ATC code. * To review and revise as necessary the ATC classification system and DDDs. * To stimulate and influence the practical use of the ATC system by co-operating with researchers in the drug utilization field. Support: The WHO Collaborating Centre for Drug Statistics Methodology was established in 1982. The Centre is situated in Oslo at the Norwegian Institute of Public Health. The Centre is funded by the Norwegian government.
Proper citation: WHO Collaborating Centre for Drug Statistics Methodology (RRID:SCR_000677) Copy
http://cmbi.bjmu.edu.cn/mirsnp
Database of human SNPs in predicted miRNA-mRNA binding sites, based on information from dbSNP135 and mirBASE18. MirSNP is highly sensitive and covers most experiments confirmed SNPs that affect miRNA function. MirSNP may be combined with researchers' own GWAS or eQTL positive data sets to identify the putative miRNA-related SNPs from traits/diseases associated variants. They aim to update the MirSNP database as new versions of mirBASE and dbSNP database become available.
Proper citation: MirSNP (RRID:SCR_001629) Copy
http://www.bioguo.org/AnimalTFDB/
A comprehensive transcription factor (TF) database in which they identified and classified all the genome-wide TFs in 50 sequenced animal genomes (Ensembl release version 60). In addition to TFs, it also collects transcription co-factors and chromatin remodeling factors of those genomes, which play regulatory roles in transcription. Here they defined the TFs as proteins containing a sequence-specific DNA-binding domain (DBD) and regulating target gene expression. Currently, the AnimalTFDB classifies all the animal TFs into 72 families according to their conserved DBDs. Gene lists of transcription factors, transcription co-factors and chromatin remodeling factors of each species are available for downloading., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: AnimalTFDB (RRID:SCR_001624) Copy
Database of information of spa-typing of MRSA, or Staphylococcus aureus, that can be used to collate and harmonize data from various geographic regions.
Proper citation: Ridom SpaServer (RRID:SCR_001460) Copy
A database that focuses on experimentally verified protein-protein interactions mined from the scientific literature by expert curators. The curated data can be analyzed in the context of the high throughput data and viewed graphically with the MINT Viewer. This collection of molecular interaction databases can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. VirusMINT explores the interactions of viral proteins with human proteins. The MINT connect viewer allows you to enter a list of proteins (e.g. proteins in a pathway) to retrieve, display and download a network with all the interactions connecting them.
Proper citation: MINT (RRID:SCR_001523) Copy
A web-based genome analysis platform that integrates proprietary functional genomic data, metabolic reconstructions, expression profiling, and biochemical and microbiological data with publicly available information. Focused on microbial genomics, it provides better and faster identification of gene function across all organisms. Building upon a comprehensive genomic database integrated with a collection of microbial metabolic and non-metabolic pathways and using proprietary algorithms, it assigns functions to genes, integrates genes into pathways, and identifies previously unknown or mischaracterized genes, cryptic pathways and gene products. . * Automated and manual annotation of genes and genomes * Analysis of metabolic and non-metabolic pathways to understand organism physiology * Comparison of multiple genomes to identify shared and unique features and SNPs * Functional analysis of gene expression microarray data * Data-mining for target gene discovery * In silico metabolic engineering and strain improvement
Proper citation: ERGO (RRID:SCR_001243) Copy
Consortium serving the diabetic complications community that sponsors annual meetings in complications-relevant scientific areas, solicits and funds pilot projects in high impact areas of complications research, and provides resources and data including animal models, protocols and methods, validation criteria, reagents and resources, histology, publications and bioinformatics for researchers conducting diabetic complications research.
Proper citation: Diabetic Complications Consortium (RRID:SCR_001415) Copy
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
http://www.homozygositymapper.org/
A web-based approach of homozygosity mapping that can handle tens of thousands markers. User can upload their own SNP genotype files to the database. Intuitive graphic interface is provided to view the homozygous stretches, with the ability of zooming into single chromosomes or user-defined chromosome regions. The underlying genotypes in all samples are displayed. The software is also integrated with our candidate gene search engine, GeneDistiller, so that users can interactively determine the most promising gene. (entry from Genetic Analysis Software)
Proper citation: HOMOZYGOSITYMAPPER (RRID:SCR_001714) Copy
http://eyelab.biostr.washington.edu/repos/eyelab_repo/
The Image Repository contains a collection of images produced by the research of John Clark's Eye Lab. Experiments include: Irradiated CP49 KO and wildtype, Hypothesis: CP49 KO mice will be more sensitive to X-irradiation than controls Huntington Mice Cataract ID, Hypothesis: Individuals can be identified by the pattern of their cataract. Alpha-Synuclein Mice, Hypothesis: Mice transgenic for the EGFP-tagged, mutant and WT strains of human alpha-synuclein gene, will provide a model for the testing of drugs on aggregation of the protein. alpha B Crystallin/SPARC DKO, Hypothesis: The absence of the chaperone protein, alpha B-Crystallin, causes a greater intensity and earlier onset in the opacifying effects of an absence of the matricellular protein, SPARC. Survey of SPARC KO and WT Survey of SPARC KO and WT Mice The repository is being built through a collaboration between the University of Washington's Department of Biological Structure, led by John Clark, and the Structural Informatics Group, led by Jim Brinkley. As an aim of the Biomedical Information Sciences Technology Initiative (BISTI), members of the Structural Informatics Group have been talking with biomedical researchers to find out their informatics needs. Tools such as this repository are being created in response to those needs. This web tool allows the researchers to add their images to a repository facilitating the organization and management of their data.
Proper citation: The Eye Lab Image Database (RRID:SCR_002038) Copy
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