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https://phenome.jax.org/centers/QTLA

Raw data from various QTL (quantitative trait loci) studies using rodent inbred line crosses. Data are available in the .csv format used by R/qtl and pseudomarker programs. In some cases analysis scripts and/or results are posted to accompany the data. These data are provided as a courtesy to the genetic mapping community and may be used for purposes of developing or testing new analysis methods or software and for meta-analysis of quantitative traits. The authors of the datasets retain individual ownership of the data. As a courtesy to the authors, please alert them in advance of any publications that result from reanalysis of these data or obtain permission prior to redistribution of data or results. In all data sets and files, the marker locations have been translated to Cox build 37 coordinates unless otherwise stated. Please consider contributing your data to the QTL Archive.

Proper citation: QTL Archive (RRID:SCR_006213) Copy   

•   Source: SciCrunch Registry

http://www.gwascentral.org/

Publicly available database of summary level findings from genetic association studies in humans, including genome wide association studies (GWAS). Previously named HGBASE, HGVbase and HGVbaseG2P.

Proper citation: GWAS Central (RRID:SCR_006170) Copy   

•   Source: SciCrunch Registry

http://researchdata.4tu.nl/en/home/

Multidisciplinary data repository for a consortium of universities in the Netherlands housing over datasets with a focus on scientific and technical data. Most data were produced by Dutch researchers including datasets from doctoral research. Users can deposit up to 1G by completing an upload form. Collection development foci include applied sciences, biomedical technology, earth sciences, and technology and construction. 4TU.Datacentrum is a collaboration of the libraries of the three leading technical universities - Delft University of Technology, Eindhoven University of Technology and the University of Twente.

Proper citation: 4TU.Datacentrum (RRID:SCR_006295) Copy   

•   Source: SciCrunch Registry

http://datastar.mannlib.cornell.edu/

A single library software prototype transitioning to a to an open-source platform ready for adoption and extension at other institutions wishing to provide research data sharing and discovery services. Datastar''''s ability to expose metadata about research datasets in a standard semantic format called Linked Data will be enhanced to support selective interchange of related information with VIVO, an open-source semantic researcher networking tool gaining prominence through adoption at multiple U.S. universities, in the federal government, and internationally.

Proper citation: DataStaR (RRID:SCR_006381) Copy   

•   Source: SciCrunch Registry

https://borealisdata.ca/dataverse/dv/?q=*

Data repository to preserve and provide access to agricultural and environmental data produced during research projects undertaken at the University of Guelph including datasets on topics such as crop yield, soil moisture, weather and agroforestry. A special emphasis is placed on research funded by Ontario Ministry of Agriculture and Food (OMAF) and MRA.

Proper citation: Agri-environmental Research Data Repository (RRID:SCR_006317) Copy   

•   Source: SciCrunch Registry

http://antibodyregistry.org/

Public registry of antibodies with unique identifiers for commercial and non-commercial antibody reagents to give researchers a way to universally identify antibodies used in publications. The registry contains antibody product information organized according to genes, species, reagent types (antibodies, recombinant proteins, ELISA, siRNA, cDNA clones). Data is provided in many formats so that authors of biological papers, text mining tools and funding agencies can quickly and accurately identify the antibody reagents they and their colleagues used. The Antibody Registry allows any user to submit a new antibody or set of antibodies to the registry via a web form, or via a spreadsheet upload.

Proper citation: Antibody Registry (RRID:SCR_006397) Copy   

•   Source: SciCrunch Registry

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

Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.

Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

•   Source: SciCrunch Registry

http://www.gigasciencejournal.com/

An online open-access open-data journal, publishing ''big-data'' studies from the entire spectrum of life and biomedical sciences whose publication format links standard manuscript publication with its affiliated database, GigaDB, that hosts all associated data, provides data analysis tools, cloud-computing resources, and a DOI assignment to every dataset. GigaScience covers not just ''omic'' type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data. Supporting the open-data movement, they require that all supporting data and source code be publicly available in a suitable public repository and/or under a public domain CC0 license in the BGI GigaScience database. Using the BGI cloud as a test environment, they also consider open-source software tools / methods for the analysis or handling of large-scale data. When submitting a manuscript, please contact them if you have datasets or cloud applications you would like them to host. To maximize data usability submitters are encouraged to follow best practice for metadata reporting and are given the opportunity to submit in ISA-Tab format.

Proper citation: GigaScience (RRID:SCR_006565) Copy   

•   Source: SciCrunch Registry

http://flybase.org/

Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.

Proper citation: FlyBase (RRID:SCR_006549) Copy   

•   Source: SciCrunch Registry

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

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

•   Source: SciCrunch Registry

http://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry

http://force11.org/

A collaboration which works to transform scholarly communications through advanced use of computers and the Web. FORCE11 advocates the digital publishing of papers in order to enable more effective scholarly communication. The virtual community also advocates the publication of software tools and research communication by means of social media channels. As such, FORCE11 provides access to information and tools for the wider scientific community.

Proper citation: FORCE11 (RRID:SCR_005334) Copy   

•   Source: SciCrunch Registry

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

Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.

Proper citation: InterPro (RRID:SCR_006695) Copy   

•   Source: SciCrunch Registry

http://www.maizegdb.org

Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.

Proper citation: MaizeGDB (RRID:SCR_006600) Copy   

•   Source: SciCrunch Registry

http://www.proteinatlas.org/

Open access resource for human proteins. Used to search for specific genes or proteins or explore different resources, each focusing on particular aspect of the genome-wide analysis of the human proteins: Tissue, Brain, Single Cell, Subcellular, Cancer, Blood, Cell line, Structure and Interaction. Swedish-based program to map all human proteins in cells, tissues, and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome.

Proper citation: The Human Protein Atlas (RRID:SCR_006710) Copy   

•   Source: SciCrunch Registry

http://www.unavco.org/

A non-profit university-governed consortium that facilitates geoscience research and education using geodesy. It rovides access to and submission of Geodetic GPS / GNSS Data, Geodetic Imaging Data, Strain and Seismic Borehole Data, and Meteorological Data. Data access web services/API provides the ability to use a command line interface to query metadata and obtain URLs to data and products. UNAVCO also provides a variety of software, including web applications, and desktop utilities for scientists, instructors, students, and others. Web-based data visualization and mapping tools provide users with the ability to view postprocessed data while web-based geodetic utilities provide ancillary information. Downloadable stand-alone software utilities include applications for configuring instruments, managing data collection, download and transfer, and performing computations on the raw data, e.g., data pre-processing or processing. The UNAVCO Facility in Boulder, Colorado is the primary operational activity of UNAVCO and exists to support university and other research investigators in their use of geophysical sensor technology for Earth sciences research. The Facility performs this task in part by archiving GNSS/GPS data and data products for current and future applications. Other data types that scientists use for Earth deformation studies are also held in the UNAVCO Archive collections. UNAVCO operates a community Archive, which provides long-term secure storage and easy retrieval of GNSS data, strain data, various derived products and related metadata. The Archive primarily stores high-precision geodetic data used for research purposes, collected under National Science Foundation and NASA sponsored projects. UNAVCO provides many learning opportunities including: Short Courses and Workshops, Educational Resources, RESESS Research Student Internships, and Technical Training.

Proper citation: UNAVCO (RRID:SCR_006706) Copy   

•   Source: SciCrunch Registry

http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

•   Source: SciCrunch Registry

https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

•   Source: SciCrunch Registry

http://www.data.gov/

Catalog of data sets that are generated and held by the Federal Government, including data, tools and resources to conduct research, develop web and mobile applications, design data visualizations, etc. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets. The data catalogs will continue to grow as datasets are added. Federal, Executive Branch data are included in the first version of Data.gov.

Proper citation: Data.gov (RRID:SCR_004712) Copy   

•   Source: SciCrunch Registry