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http://www.bclq.org/en/index.html

The primary objective of the Quebec Leukemia Cell Bank is to support basic and clinical blood cancer research. It also serves to provide an infrastructure and services aimed at facilitating the work of researchers in various fields, such as oncology, hematology and immunology in particular. Several researchers have already benefited from this infrastructure in the course of their work. The main missions of the Quebec Leukemia Cell Bank are : * To set up a bank of well-characterized human blood tumor cells. The constitutional DNA is also stored for the majority of samples. A computerized databank includes all laboratory tests performed on these specimens, as well as the corresponding clinical data. Before this bank was created, the absence of access to adequate blood tumor specimens severely hampered our researchers'' efforts to competitively pursue their work. Also, the availability of these specimens now makes it possible to establish an essential link between the basic and clinical research communities. * Provide chromosomal analysis by conventional cytogenetics and spectral karyotyping (SKY) for human and mouse cells. * Contribute to the training of specialized staff and students. The Quebec Leukemia Cell Bank is a provincial program that groups together hematologists, researchers and clinical scientists from four Quebec universities (Universit�������� Laval, McGill, Sherbrooke, Montr��������al) and Quebec research centers. The cell bank has been in operation since 2001. The purpose of this website is to raise awareness about our cell bank so we can continue to help an increasing number of researchers.

Proper citation: Quebec Leukemia Cell Bank (RRID:SCR_004916) Copy   

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http://videolectures.net/

Award-winning free and open access educational video lectures repository. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high quality didactic contents not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users' comments.

Proper citation: VideoLectures.NET (RRID:SCR_001972) Copy   

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

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http://www.germonline.org/

Cross-species microarray expression database focusing on high-throughput expression data relevant for germline development, meiosis and gametogenesis as well as the mitotic cell cycle. The database contains a unique combination of information: 1) High-throughput expression data obtained with whole-genome high-density oligonucleotide microarrays (GeneChips). 2) Sample annotation (mouse over the sample name and click on it) using the Multiomics Information Management and Annotation System (MIMAS 3.0). 3) In vivo protein-DNA binding data and protein-protein interaction data (available for selected species). 4) Genome annotation information from Ensembl version 50. 5) Orthologs are identified using data from Ensembl and OMA and linked to each other via a section in the report pages. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome. The database displays only expression data obtained with high-density oligonucleotide microarrays (GeneChips)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: GermOnline (RRID:SCR_002807) Copy   

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https://repository.niddk.nih.gov/study/21

Data and biological samples were collected by this consortium organizing international efforts to identify genes that determine an individual risk of type 1 diabetes. It originally focused on recruiting families with at least two siblings (brothers and/or sisters) who have type 1 diabetes (affected sibling pair or ASP families). The T1DGC completed enrollment for these families in August 2009. They completed enrollment of trios (father, mother, and a child with type 1 diabetes), as well as cases (people with type 1 diabetes) and controls (people with no history of type 1 diabetes) from populations with a low prevalence of this disease in January 2010. T1DGC Data and Samples: Phenotypic and genotypic data as well as biological samples (DNA, serum and plasma) for T1DGC participants have been deposited in the NIDDKCentral Repositories for future research.

Proper citation: Type 1 Diabetes Genetics Consortium (RRID:SCR_001557) Copy   

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http://www.datacite.org/

Platform for storing, finding and accessing data that provides a service for data centres to mint DOIs and store associated metadata. Their goals are to establish easier access to scientific research data on the Internet, increase acceptance of research data as legitimate, citable contributions to the scientific record and support data archiving that will permit results to be verified and re-purposed for future study. DataCite is global, with member institutions offering services and advice directly where they are needed by the researchers. While datasets are shared and accessed globally, researchers work within national funding and organizational frameworks. It therefore operates globally, with national representation. The DataCite Metadata Scheme is a list of core metadata properties chosen for the accurate and consistent identification of data for citation and retrieval purposes, along with recommended use instructions.

Proper citation: DataCite (RRID:SCR_004139) Copy   

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http://hupi.ircm.qc.ca/hupi/

The Human Proteotheque Initiative is a multidisciplinary project aimed at building a repertoire of comprehensive maps of human protein interaction networks. The information contained in the Proteotheque is made publicly available through an interactive web site that can be consulted to visualize some of the fundamental molecular connections formed in human cells and to determine putative functions of previously uncharacterized proteins based on guilt by association. The process governing the evolution of HuPI towards becoming a repository of accurate and complete protein interaction maps is described.

Proper citation: Database of the Human Proteotheque Initiative (RRID:SCR_002076) Copy   

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http://ixdb.mpimg-berlin-dahlem.mpg.de

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 08, 2013. A repository for physical mapping data of the human X chromosome that aims at providing a global view of genomic data at a chromosomal level including an integrated physical, genetic, transcript and sequence map of the human X chromosome. This implies acquiring, understanding and formatting an enormous amount of experimental results and can only be accomplished progressively. We have chosen to start the integration process with YAC maps generated by the community. These provide the basis for future higher resolution physical maps, as well as emerging transcript and sequence maps. The current content of IXDB therefore reflects this situation, with the emphasis placed on YAC mapping data. Due to their immediate value, IXDB has also started to systematically include bacterial clone contig maps and EST data. Currently IXDB does not store sequence data, although links to nucleic sequence databases are provided.

Proper citation: Integrated X Chromosome Database (RRID:SCR_003028) Copy   

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http://bc02.iis.sinica.edu.tw/gobu/manual/index.html

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy   

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https://adaptivedisclosure.wordpress.com/aida/

A generic set of components that can perform a variety of tasks, such as learn new pattern recognition models, perform specialized search on resource collections, and store knowledge in a repository. W3C standards are used to make data accessible and manageable with semantic web technologies such as OWL, RDF(S), and SKOS. The AIDA Toolkit is directed at groups of knowledge workers that cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. The server offers services for: text indexing and statistics, metadata storage and querying, thesaurus reasoning, annotation, text retrieval, spelling correction, synonym detection, and model learning.

Proper citation: AIDA Toolkit (RRID:SCR_005914) Copy   

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http://neurogenetics.nia.nih.gov

A suite of web-based open source software programs for clinical and genetic study. The aims of this software development in the Laboratory of Neurogenetics, NIA, NIH are * Build retrievable clinical data repository * Set up genetic data bank * Eliminate redundant data entries * Alleviate experimental error due to sample mix-up and genotyping error. * Facilitate clinical and genetic data integration. * Automate data analysis pipelines * Facilitate data mining for genetic as well as environmental factors associated with a disease * Provide an uniformed data acquisition framework, regardless the type of a given disease * Accommodate the heterogeneity of different studies * Manage data flow, storage and access * Ensure patient privacy and data confidentiality/security. The GERON suite consists of several self contained and yet extensible modules. Currently implemented modules are GERON Clinical, Genotyping, and Tracking. More modules are planned to be added into the suite, in order to keep up with the dynamics of the research field. Each module can be used separately or together with others into a seamless pipeline. With each module special attention has been given in order to remain free and open to the academic/government user., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GERON (RRID:SCR_008531) Copy   

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https://cabig.nci.nih.gov/tools/caTRIP

THIS RESOURCE IS NO LONGER IN SERVICE documented June 4, 2013. Allows users to query across a number of caBIG data services, join on common data elements (CDEs), and view results in a user-friendly interface. With an initial focus on enabling outcomes analysis, caTRIP allows clinicians to query across data from existing patients with similar characteristics to find treatments that were administered with success. In doing so, caTRIP can help inform treatment and improve patient care, as well as enable the searching of available tumor tissue, enable locating patients for clinical trials, and enable investigating the association between multiple predictors and their corresponding outcomes such as survival caTRIP relies on the vast array of open source caBIG applications, including: * Tumor Registry, a clinical system that is used to collect endpoint data * cancer Text Information Extraction System (caTIES), a locator of tissue resources that works via the extraction of clinical information from free text surgical pathology reports. while using controlled terminologies to populate caBIG-compliant data structures * caTissue CORE, a tissue bank repository tool for biospecimen inventory, tracking, and basic annotation * Cancer Annotation Engine (CAE), a system for storing and searching pathology annotations * caIntegrator, a tool for storing, querying, and analyzing translational data, including SNP data Requires Java installation and network connectivity.

Proper citation: caTRIP (RRID:SCR_003409) Copy   

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

The IPD-KIR database provides a centralized repository for human KIR sequences. Killer-cell Immunoglobulin-like Receptors (KIR) have been shown to be highly polymorphic at the allelic and haplotypic level. KIRs are members of the immunoglobulin superfamily (IgSF) formerly called Killer-cell Inhibitory Receptors. They are composed of two or three Ig-domains, a transmembrane region and cytoplasmic tail which can in turn be short (activatory) or long (inhibitory). The Leukocyte Receptor Complex (LRC) which encodes KIR genes has been shown to be polymorphic, polygenic and complex like the MHC.

Proper citation: IPD-KIR - Killer-cell Immunoglobulin-like Receptors (RRID:SCR_007748) Copy   

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http://www.psoriasis.org/netcommunity/act_biobank

The National Psoriasis Victor Henschel BioBank is a collection of biological samples and clinical information used by qualified scientists to further the field of psoriasis genetics. Once completed, the National Psoriasis BioBank will be the largest collection of psoriasis DNA samples in the world, moving us closer to understanding the causes of psoriatic diseases, discovering more and better treatments and finding a cure. The BioBank is currently collecting DNA from people with and without psoriasis and/or psoriatic arthritis. Simply by donating your DNA����??a blood sample and a swab of your cheek cells����??and providing us with your medical history, you can help us find a cure. Samples will be processed and stored at a private laboratory and not at the National Psoriasis Foundation. The National Psoriasis BioBank is part of the Genetic Alliance BioBank (GA BioBank), a centralized repository for the collection, storage and distribution of biological samples (including DNA, serum, cells and tissues) and clinical data for genetic researchers.

Proper citation: National Psoriasis BioBank (RRID:SCR_010537) Copy   

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https://monarchinitiative.org/

Repository of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors, and ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in context of genetic and genomic data, using semantics and statistics. Discovery system provides basic and clinical science researchers, informaticists, and medical professionals with integrated interface and set of discovery tools to reveal genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. Database that indexes authoritative information on experimental models of disease from MGI, RGD and ZFIN.

Proper citation: MONARCH Initiative (RRID:SCR_000824) Copy   

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http://www.agre.org/index.cfm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. A private repository of clinical and genetic information on families with autism. Genetic and clinical data are obtained from families that have more than one family member diagnosed with an Autism Spectrum Disorder. The biological samples, along with the accompanying clinical data, are made available to AGRE-approved researchers worldwide. As they become available, additional family pedigrees will be posted in the online catalog. Cell lines have been established for the majority of families in this collection and serum/plasma is available on a subset of the subjects until stocks are depleted. The diagnosis of autism has been made using the standard Autism Diagnostic Interview-Revised (ADI-R) algorithm and the Autism Diagnostic Observation Scale (ADOS-G). Detailed birth and medical histories (including basic dysmorphology assessments) on children as well as family and medical information for parents and unaffected siblings, are available for nearly all families. DNA, cell lines, serum, plasma and clinical information are made available to AGRE-approved researchers for analysis.

Proper citation: Autism Genetic Resource Exchange (RRID:SCR_004403) Copy   

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http://www.genomesunzipped.org/

A group blog providing expert, independent commentary on the personal genomics industry. The goal of the project is to provide genetic testing consumers with independent and informed analysis of developments in the field of genetics and the genetic testing industry. Members of Genomes Unzipped include active researchers in various fields of genetics, as well as specialists in the legal and public health issues surrounding new genomic technologies. Many of us have also been extensively involved in public communication about genetics. Members of the group have had their DNA tested with a variety of products. We have released all of these genetic data openly to the public, both as raw data and in a custom genome browser. As the project proceeds we plan to obtain more genetic tests ����?? up to and including whole genome sequencing ����?? and to continue to release these data to the world. The group is also performing analyses of our own raw genetic data to illustrate fundamental concepts in genetics, using software written both by group members and other collaborators; and we����??ll be releasing the code for that software in our new code repository. As the project expands, we����??ll be looking to add data from other volunteers to the project, as well as to collaborate with other ����??genome hackers����?? on the development of new tools for exploring genetic data.

Proper citation: Genomes Unzipped (RRID:SCR_006870) Copy   

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http://www.nesys.uio.no/Database/

This site contains the NeSys archive on structure and structure-function data about brain map transformations in the cerebellar system of the rat. This archive presents data not illustrated in the original publications, downloadable original data sets, interactive illustration sequences, including 3-D models. The repository is based on 5 original publications. The publications deal with: - organization of projections to the pontine nuclei from three cortical areas: primary and secondary somatosensory areas (SI and SII), and the primary motor cortex (MI) - organization of pontine neurons projecting to somatosensory representations in the posterior cerebellum The data are also included in the FACCS application, a relational database application with embedded analytical tools, available via the The Rodent Brain Workbench (www.rbwb.org). Sponsors: NeSys Research and Database development is supported by The Research Council of Norway, The European Community (grants QLRT-2000-02256 and QLG3-CT 1999-00763), The Norwegian Consortium for High Performance Computing, and The Jahre Foundation.

Proper citation: Database on Brain Map Transformations in Cerebellar Systems (RRID:SCR_008052) Copy   

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http://knime.org/

KNIME (Konstanz Information Miner) is a user-friendly and comprehensive Open-Source data integration, processing, analysis, and exploration platform. KNIME (naim) is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualization and reporting. The open integration platform provides over 1000 modules (nodes), including those of the KNIME community and its extensive partner network. KNIME can be downloaded onto the desktop and used free of charge. KNIME products include additional functionalities such as shared repositories, authentication, remote execution, scheduling, SOA integration and a web user interface as well as world-class support. Robust big data extensions are available for distributed frameworks such as Hadoop. KNIME is used by over 3000 organizations in more than 60 countries. The modular data exploration platform, initially developed at the University of Konstanz, Germany, enables the user to visually create data flows, execute selected analysis steps, and later investigate the results through interactive views on data and models. KNIME is a proven integration platform for tools of numerous vendors due to its open and modular API. The KNIME.com product pipeline includes an Enterprise Server, Cluster Execution, Reporting solutions, and professional KNIME support subscriptions. KNIME.com also offer services such as data analysis, hands-on training and the development of customized components for KNIME.

Proper citation: Knime (RRID:SCR_006164) Copy   

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http://cellfinder.de/

Database of mapped validated gene and protein expression, phenotype and images related to cell types. The data allow characterization and comparison of cell types and can be browsed by using the body browser and by searching for cells or genes. All cells are related to more complex systems such as tissues, organs and organisms and arranged according to their position in development. CellFinder provides long-term data storage for validated and curated primary research data and provides additional expert-validation through relevant information extracted from text. Operated under the Open Source/Access model, community and scientific networking applications will allow users to store and retrieve their data and to explore cells and their interactions on singular and complex resolution levels. The involvement of stem cell registries and banks will allow direct access to selected cells. The set up the stem cell data repository will involve three lines of action: * the acquisition of scientific data and contents * the standardized description of this data, its organization with the help of ontologies and technical implementation * the integration of existing sources/logistics and to ensure sustainable long-term operation

Proper citation: CellFinder (RRID:SCR_006598) Copy   

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