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Found 249 result(s)
The PLANKTON*NET data provider at the Alfred Wegener Institute for Polar and Marine Research is an open access repository for plankton-related information. It covers all types of phytoplankton and zooplankton from marine and freshwater areas. PLANKTON*NET's greatest strength is its comprehensiveness as for the different taxa image information as well as taxonomic descriptions can be archived. PLANKTON*NET also contains a glossary with accompanying images to illustrate the term definitions. PLANKTON*NET therefore presents a vital tool for the preservation of historic data sets as well as the archival of current research results. Because interoperability with international biodiversity data providers (e.g. GBIF) is one of our aims, the architecture behind the new planktonnet@awi repository is observation centric and allows for mulitple assignment of assets (images, references, animations, etc) to any given observation. In addition, images can be grouped in sets and/or assigned tags to satisfy user-specific needs . Sets (and respective images) of relevance to the scientific community and/or general public have been assigned a persistant digital object identifier (DOI) for the purpose of long-term preservation (e.g. set ""Plankton*Net celebrates 50 years of Roman Treaties"", handle: 10013/de.awi.planktonnet.set.495)"
Greengenes is an Earth Sciences website that assists clinical and environmental microbiologists from around the globe in classifying microorganisms from their local environments. A 16S rRNA gene database addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies.
The Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, genetic information and health care expenditures.
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to search, download, and analyze data sets generated by TCGA. It contains clinical information, genomic characterization data, and high level sequence analysis of the tumor genomes. The Data Coordinating Center (DCC) is the central provider of TCGA data. The DCC standardizes data formats and validates submitted data.
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
This database serves forest tree scientists by providing online access to hardwood tree genomic and genetic data, including assembled reference genomes, transcriptomes, and genetic mapping information. The web site also provides access to tools for mining and visualization of these data sets, including BLAST for comparing sequences, Jbrowse for browsing genomes, Apollo for community annotation and Expression Analysis to build gene expression heatmaps.
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The goals of FMGP are to: (i) sequence complete mitochondrial genomes from all major fungal lineages, (ii) infer a robust fungal phylogeny, (iii) define the origin of the fungi, their protistan ancestors, and their specific phylogenetic link to the animals, (iv) investigate mitochondrial gene expression, introns, RNAse P RNA structures, mobile elements.
The UBIRA eData repository is a multidisciplinary online service for the registration, preservation and publication of research datasets produced or collected at the University of Birmingham. It is part of the University of Birmingham Research Archive (UBIRA).
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ScholarBank@NUS is the university's Institutional Repository (IR). Its goals are to collect, preserve and showcase the research output including research data of NUS researchers and departments.
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.
Virtual Fly Brain (VFB) - an interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the Drosophila melanogaster CNS.
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eLMSG (eLibrary of Microbial Systematics and Genomics) is a web microbial library that integrates not only taxonomic information, but also genomic information and phenotypic information (including morphology, physiology, biochemistry and enzymology). The taxonomic system of eLMSG is manually curated and composed of all validly and some effectively published taxa. For each taxon, the Latin name, taxon ID (NCBI taxonomy), etymology, rank, lineage, the dates of effective and/or valid publication, feature descriptions, nomenclature type and references for the proposal and emendations during the history of the taxon are presented. Besides these data, the species taxa contain information about 16S rRNA gene and/or genome sequences. All publicly available genome data of each type species including both type and non-type strains were collected, and if needed, re-annotated using the standardized analysis pipeline. Furthermore, pan-genomic data analyses were conducted for species with ≥5 genome sequences available. Finally, for all type species, taxonomically relevant phenotypic data were extracted and curated from literatures, which were further indexed into eLMSG as searchable and analyzable data records. Taken together, eLMSG is a comprehensive web platform for studying mi- crobial systematics and genomics, potentially useful for better understanding microbial taxonomy, natural evolutionary processes and ecological relationships.
Our research focuses mainly on the past and present bio- and geodiversity and the evolution of animals and plants. The Information Technology Center of the Staatliche Naturwissenschaftliche Sammlungen Bayerns is the institutional repository for scientific data of the SNSB. Its major tasks focus on the management of bio- and geodiversity data using different kinds of information technological structures. The facility guarantees a sustainable curation, storage, archiving and provision of such data.
The Bavarian Natural History Collections (Staatliche Naturwissenschaftliche Sammlungen Bayerns, SNSB) are a research institution for natural history in Bavaria. They encompass five State Collections (zoology, botany, paleontology and geology, mineralogy, anthropology and paleoanatomy), the Botanical Garden Munich-Nymphenburg and eight museums with public exhibitions in Munich, Bamberg, Bayreuth, Eichstätt and Nördlingen. Our research focuses mainly on the past and present bio- and geodiversity and the evolution of animals and plants. To achieve this we have large scientific collections (almost 35,000,000 specimens), see "joint projects".
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
The Environmental Information Data Centre (EIDC) is part of the Natural Environment Research Council's (NERC) Environmental Data Service and is hosted by the UK Centre for Ecology & Hydrology (UKCEH). We manage nationally-important datasets concerned with the terrestrial and freshwater sciences.
Teesside University Research Data Repository links to the University's Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to be open access. https://researchdata.tees.ac.uk/about.
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Oral Cancer Gene Database is an initiative of the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai. The present database, version II, consists of 374 genes. It is developed as a user friendly site that would provide the scientist, information and external links from one place. The database is accessed through a list of all genes, and Keyword Search using gene name or gene symbol, chromosomal location, CGH (in %), and molecular weight. Interaction Network shows the interaction between genes for particular biological processes and molecular functions.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
TriTrypDB is an integrated genomic and functional genomic database for pathogens of the family Trypanosomatidae, including organisms in both Leishmania and Trypanosoma genera. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.