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Found 53 result(s)
>>>!!!<<< SMD has been retired. After approximately fifteen years of microarray-centric research service, the Stanford Microarray Database has been retired. We apologize for any inconvenience; please read below for possible resolutions to your queries. If you are looking for any raw data that was directly linked to SMD from a manuscript, please search one of the public repositories. NCBI Gene Expression Omnibus EBI ArrayExpress All published data were previously communicated to one (or both) of the public repositories. Alternatively, data for publications between 1997 and 2004 were likely migrated to the Princeton University MicroArray Database, and are accessible there. If you are looking for a manuscript supplement (i.e. from a domain other than smd.stanford.edu), perhaps try searching the Internet Archive: Wayback Machine https://archive.org/web/ . >>>!!!<<< The Stanford Microarray Database (SMD) is a DNA microarray research database that provides a large amount of data for public use.
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 CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.
Museum explorers travel to ocean depths, the peaks of the Andes, Africa's Rift Valley, the rainforests of South America, and the deserts of Central Asia. Perhaps even to a field site or research institution in your own state, territory or country. In each area, researchers collect specimens: fossils, minerals, and rocks, plants and animals, tools and artworks. Collections care professionals have meticulously preserved, labeled, cataloged, and organized items of this kind for more than 150 years. Taken together, the NMNH collections form the largest, most comprehensive natural history collection in the world. By comparing items gathered in different eras and regions, scientists learn how our world has varied across time and space.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
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.
Cary Institute data repository allows researchers to store, share and publish their research data, supplementary information and associated metadata. Each published item is assigned a Digital Object identifier (DOI), which allows the data to be citable and sustainable. This repository is a member node of DataOne.
<<<!!!<<< This repository is no longer available. The Environmental Dataset Gateway (EDG) has provided access to EPA's Open Data resources. Metadata records contributed by EPA Regions, Program Offices, and Research Laboratories that link to geospatial and non-geospatial resources (e.g., data, Web services, or applications) are now discoverable through Data.gov. https://www.re3data.org/repository/r3d100010078 >>>!!!>>>
The AOML Environmental Data Server (ENVIDS) provides interactive, on-line access to various oceanographic and atmospheric datasets residing at AOML. The in-house datasets include Atlantic Expendable Bathythermograph (XBT), Global Lagrangian Drifting Buoy, Hurricane Flight Level, and Atlantic Hurricane Tracks (North Atlantic Best Track and Synoptic). Other available datasets include Pacific Conductivitiy/Temperature/Depth Recorder (CTD) and World Ocean Atlas 1998.
>>>!!!<<< 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) >>>!!!<<<
NCEP delivers national and global weather, water, climate and space weather guidance, forecasts, warnings and analyses to its Partners and External User Communities. The National Centers for Environmental Prediction (NCEP), an arm of the NOAA's National Weather Service (NWS), is comprised of nine distinct Centers, and the Office of the Director, which provide a wide variety of national and international weather guidance products to National Weather Service field offices, government agencies, emergency managers, private sector meteorologists, and meteorological organizations and societies throughout the world. NCEP is a critical national resource in national and global weather prediction. NCEP is the starting point for nearly all weather forecasts in the United States. The Centers are: Aviation Weather Center (AWC), Climate Prediction Center (CPC), Environmental Modeling Center (EMC), NCEP Central Operations (NCO), National Hurricane Center (NHC), Ocean Prediction Center (OPC), Storm Prediction Center (SPC), Space Weather Prediction Center (SWPC), Weather Prediction Center (WPC)
MycoCosm, the DOE JGI’s web-based fungal genomics resource, which integrates fungal genomics data and analytical tools for fungal biologists. It provides navigation through sequenced genomes, genome analysis in context of comparative genomics and genome-centric view. MycoCosm promotes user community participation in data submission, annotation and analysis.
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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Our Frozen Zoo® is the largest and most diverse collection of its kind in the world. It contains over 10,000 living cell cultures, oocytes, sperm, and embryos representing nearly 1,000 taxa, including one extinct species, the po’ouli. Located at the Beckman Center for Conservation Research, the collection is also duplicated for safekeeping at a second site. The irreplaceable living cell lines, gametes, and embryos stored in the Frozen Zoo® provide an invaluable resource for conservation, assisted reproduction, evolutionary biology, and wildlife medicine.
A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.
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.
SuperDARN is an international HF radar network designed to measure global-scale magnetospheric convection by observing plasma motion in the Earth’s upper atmosphere. This network consists of more than 20 radars operating on frequencies between 8 and 20 MHz that look into the polar regions of Earth. These radars can measure the position and velocity of charged particles in our ionosphere, the highest layer of the Earth's atmosphere, and provide scientists with information regarding Earth's interaction with the space environment.
This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. In order to provide free and easy access to genome and protein sequences and associated metadata from the SARS-CoV-2, we created a dedicated Severe acute respiratory syndrome coronavirus 2 data hub. You can access the Results Table on SARS-CoV-2 data hub, by pressing "RefSeq genomes", "nucleotide" or "protein" links on announcement banner located on NCBI home page, in "Find data" navigation menu or using "Up-to-date SARS-CoV-2" shortcut button in "Search by virus" form. SARS-CoV-2 sequences is part of NCBI Virus https://www.re3data.org/repository/r3d100014322
The UniPROBE (Universal PBM Resource for Oligonucleotide Binding Evaluation) database hosts data generated by universal protein binding microarray (PBM) technology on the in vitro DNA binding specificities of proteins. This initial release of the UniPROBE database provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ('words') of length k ('k-mers'), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. In total, the database currently hosts DNA binding data for 406 nonredundant proteins from a diverse collection of organisms, including the prokaryote Vibrio harveyi, the eukaryotic malarial parasite Plasmodium falciparum, the parasitic Apicomplexan Cryptosporidium parvum, the yeast Saccharomyces cerevisiae, the worm Caenorhabditis elegans, mouse, and human. The database's web tools (on the right) include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences
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.
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.