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Found 12 result(s)
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.
The figshare service for the University of Sheffield allows researchers to store, share and publish research data. It helps the research data to be accessible by storing Metadata alongside datasets. Additionally, every uploaded item receives a Digital Object identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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.
The EZRC at KIT houses the largest experimental fish facility in Europe with a capacity of more than 300,000 fish. Zebrafish stocks are maintained mostly as frozen sperm. Frequently requested lines are also kept alive as well as a selection of wildtype strains. Several thousand mutations in protein coding genes generated by TILLING in the Stemple lab of the Sanger Centre, Hinxton, UK and lines generated by ENU mutagenesis by the Nüsslein-Volhard lab in addition to transgenic lines and mutants generated by KIT groups or brought in through collaborations. We also accept submissions on an individual basis and ship fish upon request to PIs in Europe and elsewhere. EZRC also provides screening services and technologies such as imaging and high-throughput sequencing. Key areas include automation of embryo handling and automated image acquisition and processing. Our platform also involves the development of novel microscopy techniques (e.g. SPIM, DSLM, robotic macroscope) to permit high-resolution, real-time imaging in 4D. By association with the ComPlat platform, we can support also chemical screens and offer libraries with up to 20,000 compounds in total for external users. As another service to the community the EZRC provides plasmids (cDNAs, transgenes, Talen, Crispr/cas9) maintained by the Helmholtz repository of Bioparts (HERBI) to the scientific community. In addition the fish facility keeps a range of medaka stocks, maintained by the Loosli group.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.