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Found 15 result(s)
The Structure database provides three-dimensional structures of macromolecules for a variety of research purposes and allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships.
The Saccharomyces Genome Database (SGD) provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae along with search and analysis tools to explore these data, enabling the discovery of functional relationships between sequence and gene products in fungi and higher organisms.
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The Mediterranean Germplasm Database (MGD) is the digital twin of the agri-food plant seed collection (Mediterranean Germplasm Genebank - MGG) maintained at the Institute of Biosciences and BioResources (IBBR) of the Italian National Research Council (CNR) in Bari, Italy. Overall, the collection preserves more than 59,000 accessions of 870 species from 203 genera and 39 families (mainly Poaceae, Fabaceae, Solanaceae, Brassicaceae, Asteraceae, etc.). Over 13,000 samples have been directly collected through time and georeferenced by IBBR exploration teams, while others have been acquired from other Institutions through exchange activities. The main objective of MGG is the preservation of genetic resources of herbaceous plants of interest for the Mediterranean agriculture. Particular attention is dedicated to specific segments of plant genetic resources, such as local varieties (including "typical products") or endangered agro-ecotypes, wild relatives of crops and plants potentially useful for the extraction of bioactive or biotechnological compounds. The main commitments of MGG since 1970 are: (i) the collection, conservation and distribution of PGR; (ii) the characterization and evaluation of PGRs and the analysis of their genetic structure; (ii) the selection and pre-breeding of PGR, and the recognition of useful genes.
<<<!!!<<< This repository is no longer available>>>!!!>>>. Although the web pages are no longer available, you will still be able to download the final UniGene builds as static content from the FTP site https://ftp.ncbi.nlm.nih.gov/repository/UniGene/. You will also be able to match UniGene cluster numbers to Gene records by searching Gene with UniGene cluster numbers. For best results, restrict to the “UniGene Cluster Number” field rather than all fields in Gene. For example, a search with Mm.2108[UniGene Cluster Number] finds the mouse transthyretin Gene record (Ttr). You can use the advanced search page https://www.ncbi.nlm.nih.gov/gene/advanced to help construct these searches. Keep in mind that the Gene record contains selected Reference Sequences and GenBank mRNA sequences rather than the larger set of expressed sequences in the UniGene cluster.
A database for plant breeders and researchers to combine, visualize, and interrogate the wealth of phenotype and genotype data generated by the Triticeae Coordinated Agricultural Project (TCAP).
ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
The Sequence Read Archive stores the raw sequencing data from such sequencing platforms as the Roche 454 GS System, the Illumina Genome Analyzer, the Applied Biosystems SOLiD System, the Helicos Heliscope, and the Complete Genomics. It archives the sequencing data associated with RNA-Seq, ChIP-Seq, Genomic and Transcriptomic assemblies, and 16S ribosomal RNA data.
JCVI is a world leader in genomic research. The Institute studies the societal implications of genomics in addition to genomics itself. The Institute's research involves genomic medicine; environmental genomic analysis; clean energy; synthetic biology; and ethics, law, and economics.
The Barcode of Life Data Systems (BOLD) provides DNA barcode data. BOLD's online workbench supports data validation, annotation, and publication for specimen, distributional, and molecular data. The platform consists of four main modules: a data portal, a database of barcode clusters, an educational portal, and a data collection workbench. BOLD is the go-to site for DNA-based identification. As the central informatics platform for DNA barcoding, BOLD plays a crucial role in assimilating and organizing data gathered by the international barcode research community. Two iBOL (International Barcode of Life) Working Groups are supporting the ongoing development of BOLD.
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BioMemory is the network of biological collections of the Department of Biology, Agriculture and Food Sciences (DiSBA) of the National Research Council of Italy (CNR) for bio-monitoring, biodiversity conservation, agri-food and environmental sustainability, and human well-being. The project is aimed to create a network of biobanks (i.e., scientific research collections) where data and metadata associated to biological samples of different nature are collected and stored in a systematic and well-organized way. Maintaining the existing collections will allow their future use for a number of purposes, from the genetic improvement of organisms to face environmental changes (climate-ready organisms) to the fight against epidemics and pandemics affecting humans, animals and plants.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.
The Protein database is a collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB. Protein sequences are the fundamental determinants of biological structure and function.
The NCBI Nucleotide database collects sequences from such sources as GenBank, RefSeq, TPA, and PDB. Sequences collected relate to genome, gene, and transcript sequence data, and provide a foundation for research related to the biomedical field.