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Found 46 result(s)
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
The Supreme Court Database is the definitive source for researchers, students, journalists, and citizens interested in the U.S. Supreme Court. The Database contains over two hundred pieces of information about each case decided by the Court between the 1791 and 2015 terms. Examples include the identity of the court whose decision the Supreme Court reviewed, the parties to the suit, the legal provisions considered in the case, and the votes of the Justices. The project started with Spaeth's original database. The analysis tools allow you to select and summarize cases from the Modern or Legacy Database based on your needs.
The National Deep Submergence Facility (NDSF) operates the Human Occupied Vehicle (HOV) Alvin, the Remote Operated Vehicle (ROV) Jason 2, and the Autonomous Underwater Vehicle (AUV) Sentry. Data acquired with these platforms is provided both to the science party on each expedition, and to the Woods Hole Oceanographic Institution (WHOI) Data Library.
State of the Salmon provides data on abundance, diversity, and ecosystem health of wild salmon populations specific to the Pacific Ocean, North Western North America, and Asia. Data downloads are available using two geographic frameworks: Salmon Ecoregions or Hydro 1K.
The IMEx consortium is an international collaboration between a group of major public interaction data providers who have agreed to share curation effort and develop and work to a single set of curation rules when capturing data from both directly deposited interaction data or from publications in peer-reviewed journals, capture full details of an interaction in a “deep” curation model, perform a complete curation of all protein-protein interactions experimentally demonstrated within a publication, make these interaction available in a single search interface on a common website, provide the data in standards compliant download formats, make all IMEx records freely accessible under the Creative Commons Attribution License
The DRH is a quantitative and qualitative encyclopedia of religious history. It consists of a variety of entry types including religious group and religious place. Scholars contribute entries on their area of expertise by answering questions in standardised polls. Answers are initially coded in the binary format Yes/No or categorically, with comment boxes for qualitative comments, references and links. Experts are able to answer both Yes and No to the same question, enabling nuanced answers for specific circumstances. Media, such as photos, can also be attached to either individual questions or whole entries. The DRH captures scholarly disagreement, through fine-grained records and multiple temporally and spatially overlapping entries. Users can visualise changes in answers to questions over time and the extent of scholarly consensus or disagreement.
Scholars' Mine is an online collection of scholarly and creative works produced by the faculty, staff, and students of the Missouri University of Science and Technology.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
IntAct provides a freely available, open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
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 Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. DisProt is a community resource annotating protein sequences for intrinsically disorder regions from the literature. It classifies intrinsic disorder based on experimental methods and three ontologies for molecular function, transition and binding partner.
>>>!!!<<< On June 1, 2020, the Academic Seismic Portal repositories at UTIG were merged into a single collection hosted at Lamont-Doherty Earth Observatory. Content here was removed July 1, 2020. Visit the Academic Seismic Portal @LDEO! https://www.marine-geo.org/collections/#!/collection/Seismic#summary (https://www.re3data.org/repository/r3d100010644) >>>!!!<<<
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
MatrixDB is a freely available database focused on interactions established by extracellular proteins and polysaccharides. MatrixDB takes into account the multimetric nature of the extracellular proteins (e.g. collagens, laminins and thrombospondins are multimers). MatrixDB includes interaction data extracted from the literature by manual curation in our lab, and offers access to relevant data involving extracellular proteins provided by our IMEx partner databases through the PSICQUIC webservice, as well as data from the Human Protein Reference Database. MatrixDB is in charge of the curation of papers published in Matrix Biology since January 2009
D-PLACE contains cultural, linguistic, environmental and geographic information for over 1400 human ‘societies’. A ‘society’ in D-PLACE represents a group of people in a particular locality, who often share a language and cultural identity. All cultural descriptions are tagged with the date to which they refer and with the ethnographic sources that provided the descriptions. The majority of the cultural descriptions in D-PLACE are based on ethnographic work carried out in the 19th and early-20th centuries (pre-1950).
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
LinkedEarth is an EarthCube-funded project aiming to better organize and share Earth Science data, especially paleoclimate data. LinkedEarth facilitates the work of scientists by empowering them to curate their own data and to build new tools centered around those.
RADAR service offers the ability to search for research data descriptions of the Natural Resources Institute Finland (Luke). The service includes descriptions of research data for agriculture, forestry and food sectors, game management, fisheries and environment. The public web service aims to facilitate discovering subjects of natural resources studies. In addition to Luke's research data descriptions one can search metadata of the Finnish Environment Institute (SYKE). The interface between Luke and SYKE metadata services combines Luke's research data descriptions and SYKE's descriptions of spatial datasets and data systems into a unified search service.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
Tropicos® was originally created for internal research but has since been made available to the world’s scientific community. All of the nomenclatural, bibliographic, and specimen data accumulated in MBG’s electronic databases during the past 30 years are publicly available here.
The Paleobiology Database (PaleoBioDB) is a non-governmental, non-profit public resource for paleontological data. It has been organized and operated by a multi-disciplinary, multi-institutional, international group of paleobiological researchers. Its purpose is to provide global, collection-based occurrence and taxonomic data for organisms of all geological ages, as well data services to allow easy access to data for independent development of analytical tools, visualization software, and applications of all types. The Database’s broader goal is to encourage and enable data-driven collaborative efforts that address large-scale paleobiological questions.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.