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Found 715 result(s)
The main objective of our work is to understand the pathomechanisms of late onset neurodegenerative disorders such as Huntington's, Parkinson's, Alzheimer's and Machado Joseph disease and to develop causal therapies for them. The disease causing proteins of these illnesses have been identified, but their functions in the unaffected organism are mostly unknown. Here, we have developed a strategy combining library and matrix yeast two-hybrid screens to generate a highly connected PPI network for Huntington's disease (HD).
CorrDB has data of cattle, relating to meat production, milk production, growth, health, and others. This database is designed to collect all published livestock genetic/phenotypic trait correlation data, aimed at facilitating genetic network analysis or systems biology studies.
The European Variation Archive is an open-access database of all types of genetic variation data from all species. The EVA provides access to highly detailed, granular, raw variant data from human, with other species to follow.
BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
Content type(s)
"IndExs" is a database comprising information on titles, abbreviations and bibliography of exsiccatae. Exsiccatae are defined as "published, uniform, numbered sets of preserved specimens distributed with printed labels" (Pfister 1985). Please note that there are two similar latin terms: "exsiccata, ae" is feminine and used for a set of dried specimens as defined above, whereas the term "exsiccatum, i" is neutral and used for dried specimens in general. You may search "IndExs" using title, part of the title, editor and group of organisms alone or combined. The single search result gives you an unique identifier of the series and all bibliographically important information on the series: the editor(s), title in its bibliographical correct form, standardized abbreviation of the series as to cite in specimen lists of scientific papers, the place of publication and the group(s) of organisms distributed. Additionally, the first and last number of the series as well as the corresponding year of the first and last issue are mentioned. Where preceding and / or superseding series do exist this information is linked. The database also provides access to information about the presence of the series in the herbarium M. As exsiccatae in M are not kept as bibliographically distinct units, but included in the general collections, this indication does not tell anything about the completeness of the set in M. If available, for each series one examplary label is added as image to give layout information. The images are from material located in the herbaria M (the majority), ASU, B, BM, BOUM, BR, BRIX, BUCM, CUP, DR, E, FR, G, GOET, GZU, H, HAL, IB, IBF, JE, K, KR, LD, MO, MSB, NMW, PRC, S, STU, TU, UC, UPS and several others.
Ag Data Commons (ADC) provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is that ADC will foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
In the framework of the Collaborative Research Centre/Transregio 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ (CRC/TR32,, funded by the German Research Foundation from 2007 to 2018, a RDM system was self-designed and implemented. The so-called CRC/TR32 project database (TR32DB, is operating online since early 2008. The TR32DB handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). The data is resulting from several field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected in the TR32DB.
Antarctic marine and terrestrial biodiversity data is widely scattered, patchy and often not readily accessible. In many cases the data is in danger of being irretrievably lost. establishes and supports a distributed system of interoperable databases, giving easy access through a single internet portal to a set of resources relevant to research, conservation and management pertaining to Antarctic biodiversity. provides access to both marine and terrestrial Antarctic biodiversity data.
The Landcare Research DataStore ('the DataStore') is the general data catalogue and repository for Environmental Research Data from Landcare Research. Much of Landcare Research’s research data is available through specific web pages, but many datasets sit outside these areas. This new data repository provides a mechanism for our staff to deposit and document this wider range of datasets so that they may be discovered and potentially re-used.
GLOBE (Global Collaboration Engine) is an online collaborative environment that enables land change researchers to share, compare and integrate local and regional studies with global data to assess the global relevance of their work.
The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada’s performance on key environmental sustainability issues including climate change and air quality, water quality and availability, and protected nature. The CESI website ensures that national, regional, local and international trends are readily accessible and transparently presented to all Canadians through the use of graphics, explanatory text, interactive maps and downloadable data.
Surveys provide annual information on the total, seasonal and spatial harvest of ducks, geese and other game birds in Canada, on the ecological characteristics of waterfowl harvested in Canada and the hunter activity associated with that harvest. The survey covers all of Canada divided into 23 zones and has been carried out annually since 1966. The bilingual database currently contains 9,000,000+ records.
The Cancer Immunome Database (TCIA) provides results of comprehensive immunogenomic analyses of next generation sequencing data (NGS) data for 19 solid cancers from The Cancer Genome Atlas (TCGA) and other datasource. The Cancer Immunome Atlas (TCIA) was developed and is maintained at the Division of Bioinformatics (ICBI). The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). Moreover it provides survival analyses for different types immunological parameters. TCIA will be constantly updated with new data and results.
One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
The Cellular Phenotype database stores data derived from high-throughput phenotypic studies and it is being developed as part of the Systems Microscopy Network of Excellence project. The aim of the Cellular Phenotype database is to provide easy access to phenotypic data and facilitate the integration of independent phenotypic studies. Through its interface, users can search for a gene of interest, or a collection of genes, and retrieve the loss-of-function phenotypes observed, in human cells, by suppressing the expression of the selected gene(s), through RNA interference (RNAi), across independent phenotypic studies. Similarly, users can search for a phenotype of interest and retrieve the RNAi reagents that have caused such phenotype and the associated target genes. Information about specific RNAi reagents can also be obtained when searching for a reagent ID.
Dog Genome SNP Database (DoGSD) is a data container for the variation information of dog/wolf genomes. It was designed and constructed as an SNPs detector and visualization tool to provide the research community a useful resource for the study of dog's population, evolution, phenotype and life habit.
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. The genome of SARS-CoV consists of a single, positive-strand RNA that is approximately 29,700 nucleotides long. The overall genome organization of SARS-CoV is similar to that of other coronaviruses. The reference genome includes 13 genes, which encode at least 14 proteins. Two large overlapping reading frames (ORFs) encompass 71% of the genome. The remainder has 12 potential ORFs, including genes for structural proteins S (spike), E (small envelope), M (membrane), and N (nucleocapsid). Other potential ORFs code for unique putative SARS-CoV-specific polypeptides that lack obvious sequence similarity to known proteins.
The database MORPHYLL contains quantitative and qualitative morphometric data of fossil angiosperm leaves from the Paleogene. The data are compiled from different fossil sites housed in various European Natural History Museums.
This library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The purpose of this database is to advance research on cellular activity, with the ultimate goal of improving human health.
The Erythron Database is a resource dedicated to facilitating better understanding of the cellular and molecular underpinnings of mammalian erythropoiesis. The resource is built upon a searchable database of gene expression in murine primitive and definitive erythroid cells at progressive stages of maturation.
Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.
MetaCrop is a database that summarizes diverse information about metabolic pathways in crop plants and allows automatic export of information for the creation of detailed metabolic models. MetaCrop is a database that contains manually curated, highly detailed information about metabolic pathways in crop plants, including location information, transport processes and reaction kinetics.