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Found 16 result(s)
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BioSamples stores and supplies descriptions and metadata about biological samples used in research and development by academia and industry. Samples are either 'reference' samples (e.g. from 1000 Genomes, HipSci, FAANG) or have been used in an assay database such as the European Nucleotide Archive (ENA) or ArrayExpress.
The Genomic Observatories Meta-Database (GEOME) is a web-based database that captures the who, what, where, and when of biological samples and associated genetic sequences. GEOME helps users with the following goals: ensure the metadata from your biological samples is findable, accessible, interoperable, and reusable; improve the quality of your data and comply with global data standards; and integrate with R, ease publication to NCBI's sequence read archive, and work with an associated LIMS. The initial use case for GEOME came from the Diversity of the Indo-Pacific Network (DIPnet) resource.
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Projects in the International Scientific Continental Drilling Program (ICDP) produce large amounts of data. Since the start of ICDP, data sharing has played an important part in ICDP projects, and the ICDP Operational Support Group, which provides the infrastructure for data capturing for many ICDP projects, has facilitated dissemination of data within project groups. With the online Scientific Drilling Database (SDDB; http://www.scientificdrilling.org), ICDP and GeoForschungsZentrum Potsdam (GFZ), Germany created a platform for the public dissemination of drilling data
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).
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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.
<<<!!!<<< Retirement of UniProt Metagenomic and Environmental Sequences (UniMES): UniProt has retired UniMES as there is now a resource at the EBI that is dedicated to serving metagenomic researchers. Henceforth, we recommend using the EBI Metagenomics portal instead https://www.ebi.ac.uk/metagenomics/ . In addition to providing a repository of metagenomics sequence data, EBI Metagenomics allows you to view functional and taxonomic analyses and to submit your own samples for analysis. >>>!!!>>> The UniProt Metagenomic and Environmental Sequences (UniMES) database is a repository specifically developed for metagenomic and environmental data. We provide UniMES clusters in order to obtain complete coverage of sequence space at different resolutions.
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iDog, an integrated resource for domestic dog (Canis lupus familiaris) and wild canids, provides the worldwide dog research community a variety of data services. This includes Genes, Genomes, SNPs, Breed/Disease Traits, Gene Expressions, Single Cell, Dog-Human Homolog Diseases and Literatures. In addition, iDog provides Online tools for performing genomic data visualization and analyses.
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The UniSA Data Access Portal showcases a range of Open Access research collections and datasets developed or collected by the University of South Australia. The UniSA Data Access Portal also highlights research projects and publications related to the available collections and datasets, and facilitates a variety of searches by researcher, organisation, discipline and keyword. Research collections and datasets available in Open Access can be freely downloaded and used to support your research in line with the terms of the licence under which they are made available.
The Expression Atlas provides information on gene expression patterns under different biological conditions such as a gene knock out, a plant treated with a compound, or in a particular organism part or cell. It includes both microarray and RNA-seq data. The data is re-analysed in-house to detect interesting expression patterns under the conditions of the original experiment. There are two components to the Expression Atlas, the Baseline Atlas and the Differential Atlas. The Baseline Atlas displays information about which gene products are present (and at what abundance) in "normal" conditions (e.g. tissue, cell type). It aims to answer questions such as "which genes are specifically expressed in human kidney?". This component of the Expression Atlas consists of highly-curated and quality-checked RNA-seq experiments from ArrayExpress. It has data for many different animal and plant species. New experiments are added as they become available. The Differential Atlas allows users to identify genes that are up- or down-regulated in a wide variety of different experimental conditions such as yeast mutants, cadmium treated plants, cystic fibrosis or the effect on gene expression of mind-body practice. Both microarray and RNA-seq experiments are included in the Differential Atlas. Experiments are selected from ArrayExpress and groups of samples are manually identified for comparison e.g. those with wild type genotype compared to those with a gene knock out. Each experiment is processed through our in-house differential expression statistical analysis pipeline to identify genes with a high probability of differential expression.
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<<<!!!<<< This repository is no longer available. PLEASE NOTE: Unfortunately, the Hustedt collection cannot be used at the moment. Since the collection was previously located in our section, this page can still be found here. We hope to be able to provide information on the further use of the collection shortly. https://www.awi.de/en/science/biosciences/polar-biological-oceanography/main-research-focus/hustedt-diatom-study-centre.html >>>!!!>>>
IsoArcH is an open access isotope web-database for bioarchaeological samples from prehistoric and historical periods all over the world. With 40,000+ isotope related data obtained on 13,000+ specimens (i.e., humans, animals, plants and organic residues) coming from 500+ archaeological sites, IsoArcH is now one of the world's largest repositories for isotopic data and metadata deriving from archaeological contexts. IsoArcH allows to initiate big data initiatives but also highlights research lacks in certain regions or time periods. Among others, it supports the creation of sound baselines, the undertaking of multi-scale analysis, and the realization of extensive studies and syntheses on various research issues such as paleodiet, food production, resource management, migrations, paleoclimate and paleoenvironmental changes.
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. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our 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.
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The China National GeneBank database (CNGBdb) is a unified platform for biological big data sharing and application services. CNGBdb has now integrated a large amount of internal and external biological data from resources such as CNGB, NCBI, and the EBI. There are several sub-databases in CNGBdb, including literature, variation, gene, genome, protein, sequence, organism, project, sample, experiment, run, and assembly. Based on underlying big data and cloud computing technologies, it provides various data services, including archive, analysis, knowledge search, and management authorization of biological data. CNGBdb adopts data structures and standards of international omics, health, and medicine, such as The International Nucleotide Sequence Database Collaboration (INSDC), The Global Alliance for Genomics and Health GA4GH (GA4GH), Global Genome Biodiversity Network (GGBN), American College of Medical Genetics and Genomics (ACMG), and constructs standardized data and structures with wide compatibility. All public data and services provided by CNGBdb are freely available to all users worldwide. CNGB Sequence Archive (CNSA) is the bionomics data repository of CNGBdb. CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in life science, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, and Sequence. Moreover, CNSA has achieved the correlation of sample entities, sample information, and analyzed data on some projects. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in the life science of CNGBdb, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, Sequence. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.