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Found 225 result(s)
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The database contains photographs of plants from West Africa in a broad geographical sense, mainly from the savanna regions.
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.
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.
The goal of the NeuroElectro Project is to extract information about the electrophysiological properties (e.g. resting membrane potentials and membrane time constants) of diverse neuron types from the existing literature and place it into a centralized database.
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MaxQB stores and displays collections of large proteomics projects and allows joint analysis and comparison. As a first dataset is contains proteome data of 11 different human cell lines. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted.
The Sol Genomics Network (SGN) is a clade-oriented database dedicated to the biology of the Solanaceae family which includes a large number of closely related and many agronomically important species such as tomato, potato, tobacco, eggplant, pepper, and the ornamental Petunia hybrida. SGN is part of the International Solanaceae Initiative (SOL), which has the long-term goal of creating a network of resources and information to address key questions in plant adaptation and diversification
TreeGenes is a genomic, phenotypic, and environmental data resource for forest tree species. The TreeGenes database and Dendrome project provide custom informatics tools to manage the flood of information.The database contains several curated modules that support the storage of data and provide the foundation for web-based searches and visualization tools. GMOD GUI tools such as CMAP for genetic maps and GBrowse for genome and transcriptome assemblies are implemented here. A sample tracking system, known as the Forest Tree Genetic Stock Center, sits at the forefront of most large-scale projects. Barcode identifiers assigned to the trees during sample collection are maintained in the database to identify an individual through DNA extraction, resequencing, genotyping and phenotyping. DiversiTree, a user-friendly desktop-style interface, queries the TreeGenes database and is designed for bulk retrieval of resequencing data. CartograTree combines geo-referenced individuals with relevant ecological and trait databases in a user-friendly map-based interface. ---- The Conifer Genome Network (CGN) is a virtual nexus for researchers working in conifer genomics. The CGN web site is maintained by the Dendrome Project at the University of California, Davis.
<<<!!!<<< The NCI CBIIT instance of the NBIA application was retired in March 2022. All data in the application has been transferred to The Cancer Image Archive https://www.re3data.org/repository/r3d100011559 and is available via the Access the Data > Search Radiology Portal menu item. The NBIA software is now maintained on GitHub, and can be built and deployed with the latest improvements and fixes that have been completed for TCIA. >>>!!!>>>
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references —i.e., templates— and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR —findable, accessible, interoperable, reusable— principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.
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bio.tools is a software registry for bioinformatics and the life sciences.
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Open data allows the public to access the Region's data more easily and encourages innovation in the community.
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Plastics are widely used in our economy and each year, at least 350-400 million tons are being produced at a global level. Due to poor recycling and low circular use, tens of millions of tons accumulate annually in marine and terrestrial environments. While it has become obvious that micro and macroplastics contaminate our environments recent research has identified few bacteria and fungi actively degrading plastics by enzymatic reactions. In general these are promiscuous enzymes (hydrolases) acting on low crystaline and mostly low density polymers of PET, ester-based PUR and oligomers of PA. Notably today, no enzymes have been characterized on a biochemical level for polymeric and crystaline PE, ether-based PUR, PS, PVC, PP. While many publications report on plastic degradation often, no convincing biochemical data have been published. Therefore the PAZy database lists exclusively biochemically characterized plastic-active enzymes. Predicted and putative enzymes that were not characterized on a biochemical, functional or structural level are not included in the PAZy database. The entries are manually curated.
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Sextant is a marine and coastal geographic data infrastructure. It is operated by Scientific Information Systems for the Sea (SISMER) of Ifremer (https://www.ifremer.fr/). Sextant aims to document, disseminate and promote a catalog of data related to the marine environment. For Ifremer's laboratories and partners, as well as for national and European actors working in the marine and coastal field, Sextant provides tools that promote and facilitate the archiving, consultation and availability of these geographical data. Data published by Sextant are available free or restricted. They can be used in accordance with the terms of the Creative Commons license selected by the author of data. Sextant infrastructure and the technologies used are in line with the implementation of the INSPIRE Directive and make it possible to follow the Open Data approach. Some data set published by Sextant has a DOI which enables it to be cited in a publication in a reliable and sustainable way. The long-term preservation of data filed in Sextant is ensured by Ifremer infrastructure.
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The public MorpheusML model repository collects, curates, documents and tests computational models for multi-scale and multicellular biological systems. Model must be encoded in the model description language MorpheusML. Subsections of the repository distinguish published models from contributed non-published and example models. New models are simulated in Morpheus or Artistoo independently from the authors and results are compared to published results. Successful reproduction is documented on the model's webpage. Models in this repository are included into the CI and test pipelines for each release of the model simulator Morpheus to check and guarantee reproducibility of results across future simulator updates. The model’s webpage provides a History-link to all past model versions and edits that are automatically tracked via Git. Each model is registered with a unique and persistent ID of the format M..... The model description page (incl. the biological context and key results of that model), the model’s XML file, the associated paper, and all further files (often simulation result videos) connected with that model can be retrieved via a persistent URL of the format https://identifiers.org/morpheus/M..... - for technical details on the citable ModelID please see https://registry.identifiers.org/registry/morpheus - for the model definition standard MorpheusML please see https://doi.org/10.25504/FAIRsharing.78b6a6 - for the model simulator Morpheus please see https://morpheus.gitlab.io - for the model simulator Artistoo please see https://artistoo.net/converter.html
<<<!!!<<< This repository is no longer available. >>>!!!>>> The sequencing of several bird genomes and the anticipated sequencing of many more provided the impetus to develop a model organism database devoted to the taxonomic class: Aves. Birds provide model organisms important to the study of neurobiology, immunology, genetics, development, oncology, virology, cardiovascular biology, evolution and a variety of other life sciences. Many bird species are also important to agriculture, providing an enormous worldwide food source worldwide. Genomic approaches are proving invaluable to studying traits that affect meat yield, disease resistance, behavior, and bone development along with many other factors affecting productivity. In this context, BirdBase will serve both biomedical and agricultural researchers.
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In 2018, the Ministry of Higher Education, Research and Innovation has included in its roadmap the creation of a new infrastructure called the National Biodiversity Data Centre (PNDB). The PNDB's missions are part of a FAIR (Easy to Find, Accessible, Interoperable, Reusable) approach, and consist in - providing access to datasets and metadata, associated services and products derived from the analyses - promoting scientific leadership to identify gaps and foster the emergence of community-driven systems of users and producers - facilitate the sharing of practices with other research communities, encourage the sharing of data and their reuse, and be part of the reflection on the future Earth System infrastructure. - promote coherence with national, European and international efforts concerning access to and use of biodiversity research data and the promotion of products and services. The PNDB is supported by the Muséum national d'Histoire naturelle, more specifically by the UMS 2006 PatriNat, a MNHN CNRS and AFB unit. The project is closely linked with the FRB and several of its founding institutions (AFB, BRGM, CIRAD, CNRS, Ifremer, INERIS, INRA, IRD, IRSTEA, MNHN, Univ. Montpellier).
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The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. The recently updated database offers many graphical and analytic tools to explore the data, as well as new data sets including; assessments from N.W. Africa, assessments from the Mediterranean Sea, assessments from Chile, data sets on Pacific salmon. The database is seeking collaborators to cover parts of the world that we are missing.
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The IPK stores a large volume of research results and information in various databases. The Institute of Plant Genetics and Crop Plant Research IPK Gatersleben, is a nonprofit research institution for crop genetics and molecular biology, and is part of the Leibniz Association. The mission of the IPK Gatersleben is to conduct basic and applied research in the area of plant genetics and crop plant research. The results of this work are not only of significant benefit to plant breeders and the agricultural industry, but also to the food, feed, and chemical industry. An additional research area, the use of renewable raw materials, is increasingly gaining in importance.
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In a changing climate, water raises increasingly complex challenges: concerning its quantity, quality, availability, allocation, use and significance as a habitat, resource and cultural medium. Dharmae, a ‘Data Hub of Australian Research on Marine and Aquatic Ecocultures’ brings together multi-disciplinary research data relating to water in all these forms. The term “ecoculture” guides the development of this collection and its approach to data discovery. Ecoculture recognizes that, since nature and culture are inextricably linked, there is a corresponding need for greater interconnectedness of the different knowledge systems applied to them.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDA’s services include automated archiving of imaging studies from all of the University’s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
<<<!!!<<< All user content from this site has been deleted. Visit SeedMeLab (https://seedmelab.org/) project as a new option for data hosting. >>>!!!>>> SeedMe is a result of a decade of onerous experience in preparing and sharing visualization results from supercomputing simulations with many researchers at different geographic locations using different operating systems. It’s been a labor–intensive process, unsupported by useful tools and procedures for sharing information. SeedMe provides a secure and easy-to-use functionality for efficiently and conveniently sharing results that aims to create transformative impact across many scientific domains.
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LIAS is a global information system for Lichenized and Non-Lichenized Ascomycetes. It includes several interoperable data repositories. In recent years, the two core components ‘LIAS names’ and ‘LIAS light’ have been much enlarged. LIAS light is storing phenotypic trait data. They includes > 10,700 descriptions (about 2/3 of all known lichen species), each with up to 75 descriptors comprising 2,000 traits (descriptor states and values), including 800 secondary metabolites. 500 traits may have biological functions and more than 1,000 may have phylogenetic relevance. LIAS is thus one of the most comprehensive trait databases in organismal biology. The online interactive identification key for more than 10,700 lichens is powered by the Java applet NaviKey and has been translated into 19 languages (besides English) in cooperation with lichenologists worldwide. The component ‘LIAS names’ is a platform for managing taxonomic names and classifications with currently >50,000 names, including the c. 12,000 accepted species and recognized synonyms. The LIAS portal contents, interfaces, and databases run on servers of the IT Center of the Bavarian Natural History Collections and are maintained there. 'LIAS names' and ‘LIAS light’ also deliver content data to the Catalogue of Life, acting as the Global Species Database (GSD) for lichens. LIAS gtm is a database for visualising the geographic distribution of lichen traits. LIAS is powered by the Diversity Workbench database framework with several interfaces for data management and publication. The LIAS long-term project was initiated in the early 1990s and has since been continued with funding from the DFG, the BMBF, and the EU.