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Found 11 result(s)

Conservation Genome Resource Bank for Korean Wildlife

CGRB

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Genome resource samples of wild animals, particularly those of endangered mammalian and avian species, are very difficult to collect. In Korea, many of these animals such as tigers, leopards, bears, wolves, foxes, gorals, and river otters, are either already extinct, long before the Korean biologists had the opportunity to study them, or are near extinction. Therefore, proposal for a systematic collection and preservation of genetic samples of these precious animals was adopted by Korea Science & Engineering Foundation (KOSEF). As an outcome, Conservation Genome Resource Bank for Korean Wildlife (CGRB; www.cgrb.org) was established in 2002 at the College of Veterinary Medicine, Seoul National University as one of the Special Research Materials Bank supported by the Scientific and Research Infrastructure Building Program of KOSEF. CGRB operates in collaboration with Seoul Grand Park Zoo managed by Seoul Metropolitan Government, and has offices and laboratories at both Seoul National University and Seoul Grand Park, where duplicate samples are maintained, thereby assuring a long-term, safe preservation of the samples. Thus, CGRB is the first example of the collaborative scientific infrastructure program between university and zoo in Korea.

UCSD Metabolomics Workbench

Metabolomics Workbench

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With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.

GEISHA

Gallus Expression in Situ Hybridization Analysis

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GEISHA is the online repository of in situ hybridization and corresponding metadata for genes expressed in the chicken embryo during the first six days of development.

Animal Genome Tracks on GBrowse

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Genome track alignments using GBrowse on this site are featured with: (1) Annotated and predicted genes and transcripts; (2) QTL / SNP Association tracks; (3) OMIA genes; (4) Various SNP Chip tracks; (5) Other mapping fetures or elements that are available.

Genome Warehouse

GWH

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The Genome Warehouse (GWH) is a public repository housing genome-scale data for a wide range of species and delivering a series of web services for genome data submission, storage, release and sharing.

NCBI dbVar

Database of genomic structural VARiation

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The dbVar is a database of genomic structural variation containing data from multiple gene studies. Users can browse data containing the number of variant cells from each study, and filter studies by organism, study type, method and genomic variant. Organisms include human, mouse, cattle and several additional animals. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017 ***

ArkDB

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<<<!!!<<< The ArkDB is now CLOSED With apologies to anyone who still relies on the ArkDB data system or map-drawing tools, we've had to take the difficult decision to shut down the ArkDB system. We've not been funded to maintain it for many years now and have kept it in the air as best we could with the time that we had available but recent changes in personnel and continuing updates to the underpinning libraries mean that the effort required to keep it going outweighs the perceived benefits. If you feel that this is the wrong decision, please contact us to let us know and we'll see what we can do together You can always contact us on our Roslin Bioinformatics email address (roslin.bioinformatics@roslin.ed.ac.uk) The Roslin Bioinformatics Team 21st November 2018 >>>!!!>>>

MiCroKitS

formerly: MiCroKit

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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.

mentha

the interactome browser

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mentha archives evidence collected from different sources and presents these data in a complete and comprehensive way. Its data comes from manually curated protein-protein interaction databases that have adhered to the IMEx consortium. The aggregated data forms an interactome which includes many organisms. mentha is a resource that offers a series of tools to analyse selected proteins in the context of a network of interactions. Protein interaction databases archive protein-protein interaction (PPI) information from published articles. However, no database alone has sufficient literature coverage to offer a complete resource to investigate "the interactome". mentha's approach generates every week a consistent interactome (graph). Most importantly, the procedure assigns to each interaction a reliability score that takes into account all the supporting evidence. mentha offers eight interactomes (Homo sapiens, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Escherichia coli K12, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae) plus a global network that comprises every organism, including those not mentioned. The website and the graphical application are designed to make the data stored in mentha accessible and analysable to all users. Source databases are: MINT, IntAct, DIP, MatrixDB and BioGRID.

Protist EST Program Database

PEP Database

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<<<!!!<<< The PEP database (TBestDB)--Defunct as of 2017-04 >>>!!!>>> https://megasun.bch.umontreal.ca/pepdb/pepdb.html

Expressed Sequence Tags database

dbEST

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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.