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http://www.wf4ever-project.org/

Project to addresses challenges associated with the preservation of scientific experiments in data-intensive science, including: * The definition of models to describe, in a standard way, scientific experiments by means of workflow-centric Research Objects, which comprise scientific workflows, the provenance of their executions, interconnections between workflows and related resources (e.g., datasets, publications, etc.), and social aspects related to such scientific experiments. * The collection of best practices for the creation and management of Research Objects. * The analysis and management of decay in scientific workflows. To address these challenges they are creating an architecture and tooling for the access, manipulation, sharing, reuse and evolution of Research Objects in a range of disciplines. This will result into the next generation RO-enabled myExperiment.

Proper citation: Workflow4Ever (RRID:SCR_005939) Copy   

•   Source: SciCrunch Registry

http://www.semantic-mediawiki.org/wiki/Semantic_MediaWiki

A free, open-source extension to MediaWiki - the wiki software that powers Wikipedia - that helps to search, organize, tag, browse, evaluate, and share the wiki''s content. While traditional wikis contain only text which computers can neither understand nor evaluate, SMW adds semantic annotations that allow a wiki to function as a collaborative database. Semantic MediaWiki introduces some additional markup into the wiki-text which allows users to add semantic annotations to the wiki. While this first appears to make things more complex, it can also greatly simplify the structure of the wiki, help users to find more information in less time, and improve the overall quality and consistency of the wiki. A large number of related extensions have been created that extend the ability to edit, display and browse through the data stored by SMW: the term Semantic MediaWiki is sometimes used to refer to this entire family of extensions.

Proper citation: Semantic MediaWiki (RRID:SCR_006246) Copy   

•   Source: SciCrunch Registry

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

Non-profit academic organization for research and services in bioinformatics. Provides freely available data from life science experiments, performs basic research in computational biology, and offers user training programme, manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures. Part of EMBL.

Proper citation: European Bioinformatics Institute (RRID:SCR_004727) Copy   

•   Source: SciCrunch Registry

http://www.eurordis.org/

EURORDIS is a non-governmental patient-driven alliance of patient organizations and individuals active in the field of rare diseases, dedicated to improving the quality of life of all people living with rare diseases in Europe. It is a not-for-profit organization and represents more than 479 rare disease organizations in 45 different countries (of which 25 are EU Member States), covering more than 4,000 rare diseases. It is therefore the voice of the 30 million patients affected by rare diseases throughout Europe. EURORDIS aims at improving the quality of life of people living with rare diseases in Europe through advocacy at the European level, support for research and drug development, networking patient groups, raising awareness and other actions designed to fight against the impact of rare diseases on the lives of patients and family. EURORDIS' training programs and resources are designed to strengthen the capacity of rare disease patients' representatives. Training empowers patients' representatives to advocate effectively for rare diseases at both the local and EU level. Key issues affecting patients of Rare Diseases on which we actively work: * Sustaining rare diseases as an EU public health priority * Making Rare Diseases A Public Health Priority In All Member States * Rare Diseases: An International Public Health Priority * Improving Access To Orphan Drugs * Improving Access To Quality Care * Promoting cross-border healthcare and patient mobility * Bridging Patients And Research * Genetic testing and newborn screening

Proper citation: EURORDIS (RRID:SCR_003814) Copy   

•   Source: SciCrunch Registry

http://eurofung.net/index.php?option=com_content&task=section&id=3&Itemid=4

The Eurofung project is a Coordination Action with the aim of developing a strategy to build up and maintain an integrated, sustainable European genomic database required for innovative genomics research of filamentous fungal model organisms of interest. This database will become a crystallization point for related systems and then could be integrated and conserved in a central European genomic database. The consortium counts 32 member laboratories, three of which have partner status. A Fungal Industrial Platform (FIP) of 13 members is also associated with the project. The project focuses on several filamentous fungi for different reasons. Aspergillus nidulans has a long record of use as a fungal model organism. Aspergillus niger, Trichoderma reesei and Penicillium chrysogenum are important cell factories used for the production of enzymes and metabolites including compounds such as Beta-lactams with benefits to human health. The human pathogen Aspergillus fumigatus serves not only as a model pathogen, but becomes more and more a serious threat to human health. The project contributes to create the conditions and facilities within Europe to widely apply all genomics technologies in filamentous fungal research. This will greatly expand our knowledge about filamentous fungi. This new genomics information will thus be beneficial to European biotechnology industries and help to improve the prevention and treatment of fungal disease. Expected results: The main results expected from this project are: - The contribution of the community to the manual annotation of important fungal genomes through annotation jamborees. - The realization of an integrated sustainable fungal genomic database through collaboration with bioinformatics centers and incorporation of the community data. - The realization of a fungal genomics knowledge base for the Eurofungbase community and the European fungal biotech industry through meetings, workshops and web-based information. - Intensified collaboration between the members of the network including the participating industries, thus strengthening the infrastructure for high quality fungal genomics research in Europe and furthermore determining joint research targets for the future. -Individualized training of a next generation of young scientists in fungal genomics and biotechnological research.

Proper citation: Eurofungbase (RRID:SCR_007094) Copy   

•   Source: SciCrunch Registry

http://www.gudmap.org/Resources/Ontologies.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A high-resolution ontology has been developed by members of the GUDMAP consortium to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The GUDMAP ontology encompasses Theiler stage (TS) 17-27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterized structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system.

Proper citation: GUDMAP Ontology (RRID:SCR_002637) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

•   Source: SciCrunch Registry

http://www.mighealth.net/uk/index.php/Main_Page

The MIGHEALTHNET wiki has been set up to gather information about the health of migrants and ethnic minorities in the United Kingdom. It forms part of the project MIGHEALTHNET, currently being carried out in 16 countries and co-funded by DG SANCO, the Health and Consumer Protection Directorate-General of the European Commission. We invite you to add your contributions to it and to pass on the address of this site to others who may be interested. This website is part of an EU Project that aims to give professionals, policy makers including health authorities, researchers, educators and representatives of migrant and minority groups easy access to a dynamically evolving body of knowledge and a virtual network of expertise. It will stimulate the formation of networks of individuals and organizations concerned with migrant and minority health.

Proper citation: MIGHEALTHNET (Migrant Health) (RRID:SCR_004701) Copy   

•   Source: SciCrunch Registry

http://www.genomeutwin.org/index.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study of genetic and life-style risk factors associated with common diseases based on analysis of European twins. The population cohorts used in the Genomeutwin study consist of Danish, Finnish, Italian, Dutch, English, Australian and Swedish twins and the MORGAM population cohort. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterize the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide. The participating 8 twin cohorts form a collection of over 0.6 million pairs of twins. Tens of thousands of DNA samples with informed consents for genetic studies of common diseases have already been stored from these population-based twin cohorts. Studies targeted to cardiovascular traits are now being undertaken in MORGAM, a prospective case-cohort study. MORGAM cohorts include approximately 6000 individuals, drawn from population-based cohorts consisting of more than 80 000 participants who have donated DNA samples.

Proper citation: GenomEUtwin (RRID:SCR_002843) Copy   

•   Source: SciCrunch Registry

http://bbmri-eric.eu

BBMRI is a pan-European and internationally broadly accessible research infrastructure and a network of existing and de novo biobanks and biomolecular resources. The infrastructure will include samples from patients and healthy persons, representing different European populations (with links to epidemiological and health care information), molecular genomic resources and biocomputational tools to optimally exploit this resource for global biomedical research. During the past 3 years BBMRI has grown into a 53-member consortium with over 280 associated organizations (largely biobanks) from over 30 countries, making it the largest research infrastructure project in Europe. During the preparatory phase the concept of a functional pan-European biobank was formulated and has now been presented to Member States of the European Union and for associated states for approval and funding. BBMRI will form an interface between specimens and data (from patients and European populations) and top-level biological and medical research. This can only be achieved through a distributed research infrastructure with operational units in all participating Member States. BBMRI will be implemented under the ERIC (European Research Infrastructure Consortium) legal entity. BBMRI-ERIC foresees headquarters (central coordination) in Graz, Austria, responsible for coordination of the activities of National Nodes established in participating countries. BBMRI is in the process of submitting its application to the European Commission for a legal status under the ERIC regulation, with an expected start date at the end of 2011. Major synergism, gain of statistical power and economy of scale will be achieved by interlinking, standardizing and harmonizing - sometimes even just cross-referencing - a large variety of well-qualified, up-to date, existing and de novo national resources. The network should cover (1) major European biobanks with blood, serum, tissue or other biological samples, (2) molecular methods resource centers for human and model organisms of biomedical relevance, (3) and biocomputing centers to ensure that databases of samples in the repositories are dynamically linked to existing databases and to scientific literature as well as to statistical expertise. Catalog of European Biobanks www.bbmriportal.eu Username: guest / Password: catalogue The catalogue is intended to be used as a reference for scientists seeking information about biological samples and data suitable for their research. The BBMRI catalogue of European Biobanks provides a high-level description of Europe''s biobanks characteristics using a portal solution managing metadata and aggregate data of biobanks. The catalogue can be queried by country, by biobank, by ICD-groups, by specimen types, by specific strengths, by funding and more. A search function is available for all data.

Proper citation: Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) (RRID:SCR_004226) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/mouseportal/

Database of mouse research resources at Sanger: BACs, targeting vectors, targeted ES cells, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen. The Wellcome Trust Sanger Institute generates, characterizes, and uses a variety of reagents for mouse genetics research. It also aims to facilitate the distribution of these resources to the external scientific community. Here, you will find unified access to the different resources available from the Institute or its collaborators. The resources include: 129S7 and C57BL6/J bacterial artificial chromosomes (BACs), MICER gene targeting vectors, knock-out first conditional-ready gene targeting vectors, embryonic stem (ES) cells with gene targeted mutations or with retroviral gene trap insertions, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen.

Proper citation: Sanger Mouse Resources Portal (RRID:SCR_006239) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/CAST/

A novel algorithm for low-complexity region detection and selective masking. The algorithm is based on multiple-pass Smith-Waterman comparison of the query sequence against twenty homopolymers with infinite gap penalties. The output of the algorithm is both the masked query sequence for further analysis, e.g. database searches, as well as the regions of low complexity.

Proper citation: CAST (RRID:SCR_000628) Copy   

•   Source: SciCrunch Registry

http://www.aneurist.org/

Project focused on cerebral aneurysms and provides integrated decision support system to assess risk of aneurysm rupture in patients and to optimize their treatments. IT infrastructure has been developeded for management and processing of vast amount of heterogeneous data acquired during diagnosis.

Proper citation: aneurIST (RRID:SCR_007427) Copy   

•   Source: SciCrunch Registry

http://fmf.igh.cnrs.fr/ISSAID/infevers

Registry for Familial Mediterranean Fever (FMF) and hereditary inflammatory disorders mutations. As of 2014, it includes twenty genes including: MEFV, MVK, TNFRSF1A, NLRP3, NOD2, PSTPIP1, LPIN2 and NLRP7, and contains over 1338 sequence variants. Confidential data, simple and complex alleles are accepted. For each gene, a menu offers: 1) a tabular list of the variants that can be sorted by several parameters; 2) a gene graph providing a schematic representation of the variants along the gene; 3) statistical analysis of the data according to the phenotype, alteration type, and location of the mutation in the gene; 4) the cDNA and gDNA sequences of each gene, showing the nucleotide changes along the sequence, with a color-based code highlighting the gene domains, the first ATG, and the termination codon; and 5) a download menu making all tables and figures available for the users, which, except for the gene graphs, are all automatically generated and updated upon submission of the variants. The entire database was curated to comply with the HUGO Gene Nomenclature Committee (HGNC) and HGVS nomenclature guidelines, and wherever necessary, an informative note was provided.

Proper citation: INFEVERS (RRID:SCR_007738) Copy   

•   Source: SciCrunch Registry

http://www.interaction-proteome.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 28, 2013. (URL is no longer valid) A platform for high-throughput proteomic analysis. Major objectives of IPP include the establishment of a broadly applicable platform of routine methods for the analysis of protein interaction networks in bio-medical research. A multidisciplinary approach will address; * their validation by cell biological, biochemical and biophysical methods. * their collection in a new type of public database. * their exploitation and use for in silico simulations of protein-interaction networks. The innovations generated in IPP will provide the basis for an efficient analysis and systems modeling of fundamental biological processes in health and disease. It will develop novel technology, including a high-end mass spectrometer with extremely large dynamic range, high-density peptide arrays, and improved visualization technology for light and electron microscopy. Additionally, the novel technologies will be validated with selected model systems of high relevance to medicine and biotechnology. Extensive bioinformatics support is a key element in the project to cope with the massive increase in experimental data on protein interactions obtained using the novel technologies. In particular, the efficient integration of disparate data sets represents a key challenge in proteomics and functional genomics. Therefore, the consortium includes the creator of the only European protein-interactions database, MINT. The multi-disciplinary efforts required in the scientific program of IPP are organized into four sub-projects (SP): * SP1: Tools for interaction analysis - SP1 is dedicated to the development of innovative proteomics technology to map protein-interaction networks and their cellular topology for the interaction analyses in SP2 and SP3. * SP2: Identification of interaction partners for protein domains - SP2 will generate (high throughput) data for important protein-protein interactions defined by bioinformatics and biomedical interest and by SP3, utilizing technology developed in SP1. * SP3: Functional analysis of interactions - SP3 focuses on the validation of technologies and tools developed in SP1. It will perform functional analyses of protein-interactions in medically and biochemically relevant prokaryotic and eukaryotic (mammalian) model systems. * SP4: Interactome database and modelling - SP4 provides the required bioinformatics infrastructure for the project, comprising the improvement of the public MINT database for the collection and dissemination of the interactome data; modelling and simulation of protein-interaction networks characterised in SP2 and SP3; and the dissemination of the technology developments to the scientific community.

Proper citation: Interaction Proteome Project (RRID:SCR_008043) Copy   

•   Source: SciCrunch Registry

http://www.knockoutmouse.org/

Database of the international consortium working together to mutate all protein-coding genes in the mouse using a combination of gene trapping and gene targeting in C57BL/6 mouse embryonic stem (ES) cells. Detailed information on targeted genes is available. The IKMC includes the following programs: * Knockout Mouse Project (KOMP) (USA) ** CSD, a collaborative team at the Children''''s Hospital Oakland Research Institute (CHORI), the Wellcome Trust Sanger Institute and the University of California at Davis School of Veterinary Medicine , led by Pieter deJong, Ph.D., CHORI, along with K. C. Kent Lloyd, D.V.M., Ph.D., UC Davis; and Allan Bradley, Ph.D. FRS, and William Skarnes, Ph.D., at the Wellcome Trust Sanger Institute. ** Regeneron, a team at the VelociGene division of Regeneron Pharmaceuticals, Inc., led by David Valenzuela, Ph.D. and George D. Yancopoulos, M.D., Ph.D. * European Conditional Mouse Mutagenesis Program (EUCOMM) (Europe) * North American Conditional Mouse Mutagenesis Project (NorCOMM) (Canada) * Texas A&M Institute for Genomic Medicine (TIGM) (USA) Products (vectors, mice, ES cell lines) may be ordered from the above programs.

Proper citation: International Knockout Mouse Consortium (RRID:SCR_005574) Copy   

•   Source: SciCrunch Registry

http://xldb.fc.ul.pt/biotools/rebil/goa/

A tool for assisting the GO annotation of UniProt entries by linking the GO terms present in the uncurated annotations with evidence text automatically extracted from the documents linked to UniProt entries. Platform: Online tool

Proper citation: GoAnnotator (RRID:SCR_005792) Copy   

•   Source: SciCrunch Registry

http://gopubmed.org/web/gopubmed/

A web server which allows users to explore PubMed search results with the Gene Ontology, a hierarchically structured vocabulary for molecular biology. GoPubMed submits a user''''s keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation. Platform: Online tool

Proper citation: GoPubMed (RRID:SCR_005823) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/orienTM/

A computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from a statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods.

Proper citation: orienTM (RRID:SCR_006218) Copy   

•   Source: SciCrunch Registry