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https://www.ibdgc.org/

Repository of biospecimen and phenotype data collected from Crohn's disease and ulcerative colitis cases and controls recruited at six sites throughout North America that are available to the scientific community. Phenotyping is performed using a standardized protocol, and lymphoblastoid cell lines are established for each subject. Phenotype data for each subject are collected by the Consortium's Data Coordinating Center (DCC), and phenotype data for all subjects with DNA samples are available. The resulting DNA samples have already been utilized by the Consortium to complete various association studies, including genome-wide association studies using dense genotyping arrays. Researchers can obtain DNA samples and phenotype, genotype, and pedigree data through the Data Repository. GWAS data must be requested through dbGAP. The IBDGC is involved with independent genetic research studies and actively works with members of the IBD and genetic communities on collaborative projects. They are also members of the International IBD Genetics Consortium. Phenotype Tools: The Consortium Phenotype Committee, led by Dr. Hillary Steinhart designed and validated paper forms to collect extensive phenotype data on Crohn's Disease and ulcerative colitis. Consortium phenotype tools are available for use by non-Consortium members.

Proper citation: NIDDK Inflammatory Bowel Disease Genetics Consortium (RRID:SCR_001461) Copy   

•   Source: SciCrunch Registry

https://www.upf.edu/web/ntsa/downloads/-/asset_publisher/xvT6E4pczrBw/content/2012-nonrandomness-nonlinear-dependence-and-nonstationarity-of-electroencephalographic-recordings-from-epilepsy-patients

THIS RESOURCE IS NO LONGER IN SERVICE, documented November 23, 2020; EEG data set, source code, and results from 7500 signal pairs from 5 epilepsy patients analyzed in the manuscript, Andrzejak RG, Schindler K, Rummel C. Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients. Phys. Rev. E, 86, 046206, 2012. All Matlab source codes are included in the file ASR_Sources_2012_10_16.zip. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control.

Proper citation: Bern-Barcelona EEG database (RRID:SCR_001582) Copy   

•   Source: SciCrunch Registry

http://donatelife.net/

Nonprofit alliance of national organizations and state teams dedicated to increasing organ, eye and tissue donation. Donate Life America manages and promotes the national brand for donation, Donate Life, and assists Donate Life State Teams and national partners in facilitating high-performing donor registries; developing and executing effective multi-media donor education programs; and motivating the American public to registeras organ, eye and tissue donors.

Proper citation: Donate Life America (RRID:SCR_000531) Copy   

•   Source: SciCrunch Registry

https://www.epfl.ch/labs/mmspg/research/page-58317-en-html/bci-2/bci_datasets/

A portal containing EEG datasets (in MATLAB format) and the MATLAB software that were used to produce the results in the paper named in the title of this resource. The files published can also be used as a basis for individual research on P300-based brain-computer interfaces. The system is based on the P300 evoked potential and is tested with five severely disabled and four able-bodied subjects. For four of the disabled subjects classification accuracies of 100% are obtained. The bitrates obtained for the disabled subjects range between 10 and 25 bits/min. The effect of different electrode configurations and machine learning algorithms on classification accuracy is tested.

Proper citation: An efficient P300-based brain-computer interface for disabled subjects (RRID:SCR_001584) Copy   

•   Source: SciCrunch Registry

http://www.uef.fi/en/-neurotieteet

Portal of neuroscience and neurology resources pertaining to the University of Eastern Finland.

Proper citation: UKU Neuroscience and Neurology Links (RRID:SCR_001733) Copy   

•   Source: SciCrunch Registry

http://www.genetrap.org/

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   

•   Source: SciCrunch Registry

http://wikisites.mcgill.ca/GlobalHealthGuide/index.php/Main_Page

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 15,2025. Wiki of resources useful for researchers and clinicians interested in global health. All McGill faculty, clinicians, researchers, staff and students are encouraged to use and add to these resources. If members of the research community would like to contribute to this resource, but are not a member of the McGill community, the McGill community is available for contact. An account will be created for users.

Proper citation: McGill Global Health Resource Guide (RRID:SCR_001096) Copy   

•   Source: SciCrunch Registry

http://www.gen2phen.org

Portal of GEN2PHEN project, holistic approach to genotype-to-phenotype data. Aims to unify human and model organism genetic variation databases towards increasingly holistic views into Genotype-To-Phenotype (G2P) data, and to link this system into other biomedical knowledge sources via genome browser functionality.

Proper citation: G2P Knowledge Centre (RRID:SCR_000790) Copy   

•   Source: SciCrunch Registry

http://neuromuscular.wustl.edu/

Organization portal for neuromuscular disease community and contains comprehensive listing of biological and clinical aspects of neuromuscular disorders.This knowledge base contains information on the physiology, structure of ion channels, neurotransmitters, neuroreceptors, and associated diseases. Major categories include DISORDERS & SYNDROMES, INDEXES, NEUROMUSCULAR EVALUATION, ANTIBODY TESTING and NEUROMUSCULAR DIVISION.

Proper citation: Washington University Neuromuscular Disease Center (RRID:SCR_002059) Copy   

•   Source: SciCrunch Registry

http://www.usq.edu.au/adfi

THIS RESOURCE IS NO LONGER IN SERVICE, documented on December 14, 2016. The Australian Digital Futures Institute no longer exists. It has been replaced by the USQ Digital Life Lab.

A portal for the Australian Digital Futures Institute, a cross-institutional, multidisciplinary Institute that focuses on software research for technology-enhanced innovation.

Proper citation: Australian Digital Futures Institute (RRID:SCR_001365) Copy   

•   Source: SciCrunch Registry

http://clones.haplogen.org/

Collection of isogenic human cell lines that are deficient for the expression of single genes. The current collection is based on the human cell line KBM-7 (Kotecki et al. Experimental Cell Research 1999), which is haploid for all chromosomes except chromosome 8 and a small part of chromosome 15. In these cells, genes are disrupted by the means of a retroviral gene trap. The collection is being expanded to cover the majority of expressed genes. The Human Gene Trap Mutant Collection is generated as a public-private partnership between CeMM (the Research Center for Molecular Medicine of the Austrian Academy of Sciences) and Haplogen.

Proper citation: Human Gene Trap Mutant Collection (RRID:SCR_001634) Copy   

•   Source: SciCrunch Registry

https://www.cdc.gov/fluview/?CDC_AAref_Val=https://www.cdc.gov/flu/weekly/weeklyarchives2008-2009/weekly15.htm

This page contains the Influenza Surveillance Report during 2008-2009 Influenza Season Week 15, ending April 18, 2009.

Proper citation: FluView: A Weekly Influenza Surveillance Report (RRID:SCR_001118) Copy   

•   Source: SciCrunch Registry

http://aimlab.cs.uoregon.edu/NEMO/web/

THIS RESOURCE IS NO LONGER IN SERVICE. NIH tombstone webpage lists Project Period : 2009 - 2013. NIH funded project to create EEG and MEG ontologies and ontology based tools. These resources will be used to support representation, classification, and meta-analysis of brain electromagnetic data. Three pillars of NEMO are: DATA, ONTOLOGY, and DATABASE. NEMO data consist of raw EEG, averaged EEG (ERPs), and ERP data analysis results. NEMO ontologies include concepts related to ERP data (including spatial and temporal features of ERP patterns), data provenance, and cognitive and linguistic paradigms that were used to collect data. NEMO database portal is large repository that stores NEMO consortium data, data analysis results, and data provenance. EEG and MEG ontologies and ontology-based tools to support representation, classification, and meta-analysis of brain electromagnetic data. Raw EEG and ERP data may be uploaded to the NEMO FTP site., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neural ElectroMagnetic Ontologies (NEMO) Project (RRID:SCR_002001) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/skewer/

Software program for adapter trimming that is specially designed for processing Illumina paired-end sequences.

Proper citation: skewer (RRID:SCR_001151) Copy   

•   Source: SciCrunch Registry

https://github.com/princelab/mspire-simulator

A free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components.

Proper citation: Mspire-Simulator (RRID:SCR_001431) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/sanford-burnham-medical-research-institute--2

A portal which lists the various labs and facilities that are part of the Sanford-Burnham Medical Research Institute.

Proper citation: Sanford-Burnham Medical Research Institute Labs and Facilities (RRID:SCR_001029) Copy   

•   Source: SciCrunch Registry

https://orwh.od.nih.gov/

The mission of the Office of Research on Women's Health (ORWH) is to stimulate and encourage meritorious research on women's health, including the role of sex and gender in health and disease. The priorities signify approaches and areas for which there is a need to stimulate and encourage research on women's health, or sex/gender factors, and the advancement of women in biomedical research careers. These research priorities are not an exclusive list of research areas important to women's health; therefore other innovative or significant research areas should also be considered. The following four overarching themes are important for addressing research on women's health: Lifespan, Sex/Gender Determinants, Health Disparities/Differences and Diversity, ad Interdisciplinary Research. Special Areas of Emphasis - Prevention/Treatment: from basic biological factors, including identifying and validating biomarkers, to risk and its applications to disease prevention, early detection, and treatment. - Sex and Genetics/Pharmacogenomics: genetic, molecular, and cellular basis for action of pharmacologic agents known to have different effects in females than in males. Research on effects of sex as a modifier of gene function and response is under-investigated. Sponsors: This research is funded by the NAtional Institutes of Health.

Proper citation: Office of Research on Womens Health: Reseach (RRID:SCR_001822) Copy   

•   Source: SciCrunch Registry

http://lbgi.fr/balibase/

A collection of high quality multiple sequence alignments for objective, comparative studies of alignment algorithms. The alignments are constructed based on 3D structure superposition and manually refined to ensure alignment of important functional residues. A number of subsets are defined covering many of the most important problems encountered when aligning real sets of proteins. It is specifically designed to serve as an evaluation resource to address all the problems encountered when aligning complete sequences. The first release provided sets of reference alignments dealing with the problems of high variability, unequal repartition and large N/C-terminal extensions and internal insertions. Version 2.0 of the database incorporates three new reference sets of alignments containing structural repeats, trans-membrane sequences and circular permutations to evaluate the accuracy of detection/prediction and alignment of these complex sequences.
Within the resource, users can look at a list of all the alignments, download the whole database by ftp, get the "c" program to compare a test alignment with the BAliBASE reference (The source code for the program is freely available), or look at the results of a comparison study of several multiple alignment programs, using BAliBASE reference sets.

Proper citation: BAliBASE (RRID:SCR_001940) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/iowa3/

Software for real-time parametric statistical analysis of functional MRI (fMRI) data. The system that combines a general architecture for sampling and time-stamping relevant information channels in fMRI (image acquisition, stimulation, subject responses, cardiac and respiratory monitors, etc.) and an efficient approach to manipulating these data, featuring incremental subsecond multiple linear regression. The advantages of the system are the simplification of event timing and efficient and unified data formatting. Substantial parametric analysis can be performed and displayed in real-time. Immediate (replay) and delayed off-line analysis can also be performed with the same interface. The system provides a time-accounting infrastructure that readily supports standard and innovative approaches to fMRI.

Proper citation: I/OWA (RRID:SCR_000858) Copy   

•   Source: SciCrunch Registry