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http://www.dna-network.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 6, 2011. A project to collect, store and study DNA samples from tens of thousands of healthy volunteers and patients with diseases of major public importance. It aims to identify genes that are risk factors for the conditions. The network consists of 13 collections led by different clinicians throughout the UK. At its heart is an archive infrastructure which manages the DNA and the information associated with it. The European Collection of Cell Cultures in Porton Down handles the blood, peripheral blood lymphocytes and EBV-transformed cell lines, while the Centre for Integrated Genomic Medical Research at Manchester University manages the DNA. These banked samples are available to UK and international researchers, who can examine data and set up collaborative work by registering at the DNA Network's website. The conditions for which samples are currently collected and stored are: Acute leukemia, Asthma and eczema, Late onset Alzheimer's disease, Breast cancer, Colorectal cancer, Coronary artery disease, Glomerulonephritis, Hypertension, Age-related macular degeneration, Multiple sclerosis, Parkinson's disease, Type 2 diabetes, Unipolar depression.

Proper citation: UK DNA Banking Network (RRID:SCR_010619) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29350&a=31589&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The aim of EXT (extinction) is to investigate the relation between specific genetic variations and cognitive control process in fear. Blood samples will be collected from about 300 healthy, young individuals (age 18-35).

Proper citation: KI Biobank - EXT (RRID:SCR_008875) Copy   

•   Source: SciCrunch Registry

http://www.cartagene.qc.ca/en

As both the public health survey of Quebec, and the Quebec resource for scientists interested in personalized medicine, genomics and public health, this public resource operates under a governance framework and consists of a databank and a biobank. The database contains environmental, demographic and health data. The biobank contains DNA, blood and urine samples. Access to CARTaGENE will be granted to researchers who are seeking to better understand how genes interact with other genes, with the environment and with lifestyle factors. They have collected in-depth information on over 20 000 Quebecers, including 446 sociodemographic, life-style and health data, 190 physiological parameters, 22 types of biochemical analyses and 41 types of haematological analyses. They have also collected 11 types of blood, plasma, serum and urine samples from most participants. Genealogical reconstruction of recruited participants, in collaboration with BALSAC Project, is also possible. CARTaGENE data and samples include the following: Health Questionnaire, Physical measures, Biochemical and hematological analysis, Biological samples stored in the Biobank. CARTagene is currently contacting participants (who have agreed to be recontacted) to collect additional data on environmental exposure. Data on dietary habits will be collected during the second phase of this component which will begin soon. Any scientific researcher working in a public or private organization at the national or international level may apply for access to CARTaGENE samples or data.

Proper citation: CARTaGENE (RRID:SCR_010614) Copy   

•   Source: SciCrunch Registry

http://www.sapaldia.net/en/

SAPALDIA (Swiss study on Air Pollution and Lung Disease in adults) is a multi-center study in eight geographic areas representing the range of environmental, meteorological and socio-demographic conditions of Switzerland, which studies the effects of air pollution on the respiratory and cardiovascular health in adults. Local centers are: Aarau, Basel, Davos, Geneva, Lugano, Montana, Payerne, and Wald. It was initiated in 1991 (SAPALDIA 1) with a follow-up assessment in 2002 (SAPALDIA 2). This study has allowed to assess 1) prevalence and development of major respiratory and allergic symptoms and diseases and the age-related decline in lung function, 2) the distribution of heart rate variability in the general population over age 50, 3) the association of these health indicators with individual long term exposure to air pollution, other toxic inhalants, life style and molecular factors. Another follow-up examination (SAPALDIA 3) started in January 2010. This study is well positioned to address crucial questions of air pollution epidemiology and important environmental health policy-related questions in the coming years. When SAPALDIA was initiated in 1991, 9''''651 subjects, aged 18 to 60 years, were recruited for a detailed computer-based interview and more than 90% of them underwent lung function and atopy testing. More than 7''''000 of the subjects had bronchial reactivity tested by a methacholine challenge. SAPALDIA shares parts of its study protocol with the European Community Respiratory Health Survey (ECRHS) with which it is linked through the study center of Basel. Since 1991 SAPALDIA has been carefully following address histories of its participants. In the 2002 follow-up, 8''''047 (83%) provided health information, 6''''528 persons underwent physical re-examination, and 6''''345 provided blood samples to establish an extensive blood, plasma, serum and DNA bank. In addition, 1''''813 subjects aged 50 or older participated in 24h-ECG Holter monitoring to provide detailed data on parameters of heart rate variability. With the inclusion of cardiovascular endpoints, SAPALDIA is one of the first studies examining effects from long-term exposure to air pollution on cardiovascular health parameters as well as mutual influence between the respiratory and the cardiovascular system. The SAPALDIA bio-bank has allowed scientific publications on the association between some genetic profiles (gene polymorphism) and the propensity to develop asthma, allergic diseases, or accelerated lung function decline with age. Ongoing studies are focusing on gene-environment interactions a crucial question to understand why some persons suffer more from the effect of air pollution than others.

Proper citation: SAPALDIA (RRID:SCR_013416) Copy   

•   Source: SciCrunch Registry

http://www.seattle.eric.research.va.gov/VETR/biospecimen_repository.asp

The Vietnam Era Twin (VET) Registry maintains a repository of biological specimens obtained from Registry members. The VET Registry Biospecimen Repository includes DNA, plasma, and serum samples obtained from selected VET Registry members. As the VET Registry is a national resource for studies investigating genetic and non-genetic influences on health and disease in middle age men, this enhances the value of the information collected from VET Registry members to the research community. The VET Registry has developed a general system of protocols for the collection and storage of biological specimens that assures confidentiality for all participants. The biological specimens currently in use are stored at the R&D Core Laboratory at the VA Puget Sound Health Care System (VAPSHCS) in Seattle, WA. The R&D Core Laboratory performs DNA extraction procedures and separates out DNA, plasma, and serum for testing and storage. It is important to note that Core Laboratory staff has absolutely no phenotypic (non-genetic) information about VET Registry members, as the lab is completely blinded to the identity, disease characteristics, and any other research data collected from VET Registry members. The Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) Core Laboratory is located at the VA Boston Health Care System in Boston, MA, and serves as the long-term storage site for the VET Registry Biospecimen Repository. Before a VET Registry member decides whether to participate in the Biospecimen Repository, the procedures, confidentiality safeguards, and potential risks are explained in great detail. To be able to accommodate the wishes of members, a so-called layered consent process is used which allows members to choose from several options with regard to how their biological specimen will be used in current or future research studies. Such options may include: 1) not having their samples used for any testing beyond the immediate goals of the study; 2) allowing for future testing of their samples restricted to the study for which they provided the sample; or 3) allowing unrestricted future research use of their samples. Members are informed that any future use of their samples would have to be approved by the VET Registry, in addition to an independent ethics committee that protects the rights and welfare of research subjects, this board is more commonly known as an Institutional Review Board or IRB. Confidentiality safeguards include assigning code numbers, as opposed to name or other personal information, on all biological specimens. Zygosity Testing The accuracy of DNA testing makes it the best method for determining zygosity, identical (monozygotic) versus fraternal (non-identical or dizygotic), in VET Registry twin members. The use of DNA for zygosity testing is only performed when both members of a twin pair agree to the testing. Other Genetic Testing for specific genes will not necessarily involve providing the participants with test results.

Proper citation: Vietnam Era Twin Registry Biospecimen Repository (RRID:SCR_008808) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/onemap/index.html

Software environment for constructing linkage maps in outcrossing plant species, using full-sib families derived from two outbreed (non-inbreeding) parent plants. (entry from Genetic Analysis Software)

Proper citation: R/ONEMAP (RRID:SCR_009371) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/hapassoc/index.html

Software application using a likelihood approach to inference of haplotype and nongenetic effects and their interactions in generalized linear models of disease penetrance, when haplotype phase is unknown for some subjects. Parameter estimates are obtained by use of an expectation-maximization (EM) algorithm and standard errors are calculated using Louis'' formula. (entry from Genetic Analysis Software)

Proper citation: R/HAPASSOC (RRID:SCR_009365) Copy   

•   Source: SciCrunch Registry

http://www.cs.cmu.edu/~genome/FAST-MAP.html

Fluorescent allele-calling software toolkit: a computer software for fully automated microsatellite genotyping. (entry from Genetic Analysis Software)

Proper citation: FASTMAP (1) (RRID:SCR_008346) Copy   

•   Source: SciCrunch Registry

https://cibersort.stanford.edu/

Software tool to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data. Used for characterizing cell composition of complex tissues from their gene expression profiles, large scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets.

Proper citation: CIBERSORT (RRID:SCR_016955) Copy   

•   Source: SciCrunch Registry

http://www.jax.org/mmrrc/

Center for mutant mouse research and distribution. The objectives of the JAX MMRRC are to: identify and evaluate biomedically-significant mice, import/acquire and archive mouse strains, distribute mouse strains, and operate a control program to ensure genetic stability.

Proper citation: Mutant Mouse Resource and Research Center - Jackson Laboratory (RRID:SCR_016446) Copy   

•   Source: SciCrunch Registry

http://genome.ufl.edu/mapper/

A platform composed of three modules: the Database, the Search Engine, and rSNPs, for the computational identification of transcription factor binding sites (TFBSs) in multiple genomes, that combines TRANSFAC and JASPAR data with the search power of profile hidden Markov models (HMMs). The Database contains putative TFBSs found in the upstream sequences of genes from the human, mouse and D.melanogaster genomes. For each gene, they scanned the region from 10,000 base pairs upstream of the transcript start to 50 base pairs downstream of the coding sequence start against all their models. Therefore, the database contains putative binding sites in the gene promoter and in the initial introns and non-coding exons. Information displayed for each putative binding site includes the transcription factor name, its position (absolute on the chromosome, or relative to the gene), the score of the prediction, and the region of the gene the site belongs to. If the selected gene has homologs in any of the other two organisms, the program optionally displays the putative TFBSs in the homologs. The Search Engine allows the identification, visualization and selection of putative TFBSs occurring in the promoter or other regions of a gene from the human, mouse, D.melanogaster, C.elegans or S.cerevisiae genomes. In addition, it allows the user to upload a sequence to query and to build a model by supplying a multiple sequence alignment of binding sites for a transcription factor of interest. rSNPs MAPPER is designed to identify Single Nucleotide Polymorphisms (SNPs) that may have an effect on the presence of one or more TFBSs.

Proper citation: MAPPER - Multi-genome Analysis of Positions and Patterns of Elements of Regulation (RRID:SCR_003077) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org/codehop.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.Service to design PCR primers from protein multiple sequence alignments. NOTICE: This version of CODEHOP is no longer maintained.

Proper citation: CODEHOP (RRID:SCR_002898) Copy   

•   Source: SciCrunch Registry

http://genecards.org

Database of human genes that provides concise genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. Information featured in GeneCards includes orthologies, disease relationships, mutations and SNPs, gene expression, gene function, pathways, protein-protein interactions, related drugs and compounds and direct links to cutting edge research reagents and tools such as antibodies, recombinant proteins, clones, expression assays and RNAi reagents.

Proper citation: GeneCards (RRID:SCR_002773) Copy   

•   Source: SciCrunch Registry

http://bibiserv.techfak.uni-bielefeld.de/genefisher2/

A web-based program for designing degenerate primers. The procedure leads to isolation of genes in a target organism using multiple alignments of related genes from different organisms. The term gene fishing refers to the technique where PCR is used to isolate a postulated but unknown target sequence from a pool of DNA.

Proper citation: GeneFisher (RRID:SCR_003060) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.charite.de/synsysnet/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. A curated database for synaptic proteins that provides adequate definitions of pre- and post-synaptic proteins, proteins present in sub-domains of the synapse, e.g. the synaptic vesicle and associated proteins, lipid rafts and postsynaptic density. In addition to data that was and will be gathered from the experiments conducted within SynSys - A European expertise Network on building the synapse, they have extracted and manually curated all relevant data on these proteins from other sources and provided an ontology for these. Novel splice forms are being identified that can be matched with proteomics data. Information on proteins, their 3D structure, binding small molecules Protein-Protein-Interactions (PPIs) and Compound-Protein-Interactions are integrated. Proteins or compounds can be searched and Interactive Networks can be visualized. The point Diseases present neurological diseases, to illustrate the role of SynSysNet in the medication.

Proper citation: SynSysNet (RRID:SCR_003180) Copy   

•   Source: SciCrunch Registry

http://www.lipidmaps.org/data/proteome/LMPD.php

Database of lipid related proteins representing human and mouse proteins involved in lipid metabolism. Collection of lipid related genes and proteins contains data for genes and proteins from Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae, Caenorhabditis elegans, Escherichia coli, Macaca mulata, Drosophila melanogaster, Arabidopsis thaliana and Danio rerio.

Proper citation: LIPID MAPS Proteome Database (RRID:SCR_003062) Copy   

•   Source: SciCrunch Registry

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

Automated system for constructing putative homology groups from complete gene sets of wide range of eukaryotic species. Databse that provides system for automatic detection of homologs, including paralogs and orthologs, among annotated genes of sequenced eukaryotic genomes. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences. Reports include homology and phenotype information drawn from Online Mendelian Inheritance in Man, Mouse Genome Informatics, Zebrafish Information Network, Saccharomyces Genome Database and FlyBase.

Proper citation: HomoloGene (RRID:SCR_002924) Copy   

•   Source: SciCrunch Registry

http://cubic.bioc.columbia.edu/db/LOC3d/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. LOC3d is a database of predicted subcellular localization for eukaryotic proteins of known 3-D structure taken from the Protein Databank. Subcellular localization is currently predicted using four different methods: predictNLS (nuclear localization signal), LOChom (using homology), LOCkey (using keywords) and LOC3d (neural network based prediction). The reported localization is based on the method which predicts localization of a given protein with the highest confidence. LOCtree is a novel system of support vector machines (SVMs) that predict the subcellular localization of proteins, and DNA-binding propensity for nuclear proteins, by incorporating a hierarchical ontology of localization classes modeled onto biological processing pathways. Biological similarities are incorporated from the description of cellular components provided by the gene ontology consortium (GO). GO definitions have been simplified and tailored to the problem of protein sorting. Technically the ontology has been implemented using a decision tree with SVMs as the nodes. LOCtree, was extremely successful at learning evolutionary similarities among subcellular localization classes and was significantly more accurate than other traditional networks at predicting subcellular localization. Whenever available, LOCtree also reports predictions based on the following: 1) Nuclear localization signals found by PredictNLS, 2) Localization inferred using Prosite motifs and Pfam domains found in the protein, and 3) SWISS-PROT keywords associated with a protein. Localization is inferred in the last two cases using the entropy-based LOCkey algorithm. Additional information can be found in the LOCtree manuscript and associated PredictNLS and LOCkey publications.

Proper citation: Database oDatabase of Predicted Subcellular Localization for Eukaryotic PDB Chainsf Predicted Subcellular Localization for Eukaryotic PDB Chains (RRID:SCR_002831) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/tools/ESE

A web-based analysis service for identifying exonic splicing enhancers in eukaryotic genes. ESEfinder accept sequences in the FASTA format. A typical mammalian gene is composed of several relatively short exons that are interrupted by much longer introns. To generate correct mature mRNAs, the exons must be identified and joined together precisely and efficiently, in a process that requires the coordinated action of five small nuclear (sn)RNAs (U1, U2, U4, U5 and U6) and more than 60 polypeptides. The inaccurate recognition of exon/intron boundaries or the failure to remove an intron generates aberrant mRNAs that are either unstable or code for defective or deleterious protein isoforms. Exonic enhancers are thought to serve as binding sites for specific serine/arginine-rich (SR) proteins, a family of structurally related and highly conserved splicing factors characterized by one or two RNA-recognition motifs (RRM) and by a distinctive C-terminal domain highly enriched in RS dipeptides (the RS domain). The RRMs mediate sequence-specific binding to the RNA, and so determine substrate specificity, whereas the RS domain appears to be involved mainly in protein-protein interactions. SR proteins bound to ESEs can promote exon definition by directly recruiting the splicing machinery through their RS domain and/or by antagonizing the action of nearby silencer elements. Sponsors: ESEfinder is supported by the Cold Spring Harbor Laboratory.

Proper citation: Exonic Splicing Enhancer Finder (RRID:SCR_002835) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ipd/

A set of specialist databases related to the study of polymorphic genes in the immune system. The IPD project works with specialist groups or nomenclature committees who provide and curate individual sections before they are submitted to IPD for online publication. The IPD project stores all the data in a set of related databases. IPD currently consists of four databases: * IPD-KIR, contains the allelic sequences of Killer-cell Immunoglobulin-like Receptors, * IPD-MHC, is a database of sequences of the Major Histocompatibility Complex of different species; * IPD-human platelet antigens, alloantigens expressed only on platelets and * IPD-ESTDAB, which provides access to the European Searchable Tumour cell-line database, a cell bank of immunologically characterized melanoma cell lines.

Proper citation: IPD - Immuno Polymorphism Database (RRID:SCR_003004) Copy   

•   Source: SciCrunch Registry