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Found 26 result(s)
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
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Avibase is an extensive database information system about all birds of the world, containing over 60 million records about 10,000 species and 22,000 subspecies of birds, including distribution information, taxonomy, synonyms in several languages and more. This site is managed by Denis Lepage and hosted by Bird Studies Canada, the Canadian copartner of Birdlife International. Avibase has been a work in progress since 1992 and I am now pleased to offer it as a service to the bird-watching and scientific community.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
IntAct provides a freely available, open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. In addition to capturing the core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and clear indications of the quality of annotation in the form of evidence attribution of experimental and computational data. The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. The UniProt Knowledgebase,is an expertly and richly curated protein database, consisting of two sections called UniProtKB/Swiss-Prot and UniProtKB/TrEMBL.
The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc).
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The IDR makes datasets that have never previously been accessible publicly available, allowing the community to search, view, mine and even process and analyze large, complex, multidimensional life sciences image data. Sharing data promotes the validation of experimental methods and scientific conclusions, the comparison with new data obtained by the global scientific community, and enables data reuse by developers of new analysis and processing tools.
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coastMap offers campaign data, model analysis and thematic maps predominantly in the Biogeosciences. Spotlights explain in a nutshell important topics of the research conducted for the interested public. The portal offers applications to visualise and download field and laboratory work and to connect the information with interactive maps. Filter functions allow the user to search for general topics like a marine field of interest or single criteria, for example a specific ship campaign or one of 1000 measured parameters.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are 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. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
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ProteomicsDB started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and cell line viability data.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.
The CATH database is a hierarchical domain classification of protein structures in the Protein Data Bank. Protein structures are classified using a combination of automated and manual procedures. There are four major levels in the CATH hierarchy; Class, Architecture, Topology and Homologous superfamily.
Harmonized, indexed, searchable large-scale human FG data collection with extensive metadata. Provides scalable, unified way to easily access massive functional genomics (FG) and annotation data collections curated from large-scale genomic studies. Direct integration (API) with custom / high-throughput genetic and genomic analysis workflows.
InnateDB is a publicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures an improved coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralised resource. The database can be mined as a knowledgebase or used with our integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.
arrayMap is a repository of cancer genome profiling data. Original) from primary repositories (e.g. NCBI GEO, EBI ArrayExpress, TCGA) is re-processed and annotated for metadata. Unique visualization of the processed data allows critical evaluation of data quality and genome information. Structured metadata provides easy access to summary statistics, with a focus on copy number aberrations in cancer entities.
The Progenetix database provides an overview of copy number abnormalities in human cancer from currently 32548 array and chromosomal Comparative Genomic Hybridization (CGH) experiments, as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. The cancer profile data in Progenetix was curated from 1031 articles and represents 366 different cancer types, according to the International classification of Diseases in Oncology (ICD-O).
The BioImage Archive stores and distributes life sciences imaging datasets. It supports deposition of biological imaging data associated with publications for the whole research community, as well as reference imaging datasets. All data deposited to the BioImage Archive is made openly accessible to the scientific community.
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!!! <<< this record is no longer maintained, please use https://www.re3data.org/repository/r3d100011876 or https://www.re3data.org/repository/r3d100011647 >>> !!!: e!DAL stands for electronic Data Archive Library. It is a lightweight open source software software framework for publishing and sharing research data. e!DAL was developed based on experiences coming from decades of research data management and has grown towards being a general data archiving and publication infrastructure [https://doi.org/10.1186/1471-2105-15-214]. First research data repository is "Plant Genomics and Phenomics Research Data Repository" [https://doi.org/10.1093/database/baw033].
The Deep Carbon Observatory (DCO) is a global community of multi-disciplinary scientists unlocking the inner secrets of Earth through investigations into life, energy, and the fundamentally unique chemistry of carbon. Deep Carbon Observatory Digital Object Registry (“DCO-VIVO”) is a centrally-managed digital object identification, object registration and metadata management service for the DCO. Digital object registration includes DCO-ID generation based on the global Handle System infrastructure and metadata collection using VIVO. Users will be able to deposit their data into the DCO Data Repository and have that data discoverable and accessible by others.
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The ZFMK Biodiversity Data Center is aimed at hosting, archiving, publishing and distributing data from biodiversity research and zoological collections. The Biodiversity Data Center handles and curates data on: - The specimens of the institutes collection, including provenance, distribution, habitat, and taxonomic data. - Observations, recordings and measurements from field research, monitoring and ecological inventories. - Morphological measurements, descriptions on specimens, as well as - Genetic barcode libraries, and - Genetic and molecular research data associated with specimens or environmental samples. For this purpose, suitable software and hardware systems are operated and the required infrastructure is further developed. Core components of the software architecture are: The DiversityWorkbench suite for managing all collection-related information. The Digital Asset Management system easyDB for multimedia assets. The description database Morph·D·Base for morphological data sets and character matrices.