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Found 9 result(s)
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. Our activities in the field of medical image analysis and data modelling are visible in a number of projects we are running. CancerData is offering several datasets. They are grouped in collections and can be public or private. You can search for public datasets in the NBIA (National Biomedical Imaging Archive) image archives without logging in.
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 European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature.
The Sequence Read Archive stores the raw sequencing data from such sequencing platforms as the Roche 454 GS System, the Illumina Genome Analyzer, the Applied Biosystems SOLiD System, the Helicos Heliscope, and the Complete Genomics. It archives the sequencing data associated with RNA-Seq, ChIP-Seq, Genomic and Transcriptomic assemblies, and 16S ribosomal RNA data.
GermOnline 4.0 is a cross-species database gateway focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome.
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.
The THEMIS mission is a five-satellite Explorer mission whose primary objective is to understand the onset and macroscale evolution of magnetospheric substorms. The five small satellites were launched together on a Delta II rocket and they carry identical sets of instruments including an electric field instrument (EFI), a flux gate magnetometer (FGM), a search coil magnetometer (SCM), a electro-static analyzer, and solid state telescopes (SST). The mission consists of several phases. In the first phase, the spacecraft will all orbit as a tight cluster in the same orbital plane with apogee at 15.4 Earth radii (RE). In the second phase, also called the Dawn Phase, the satellites will be placed in their orbits and during this time their apogees will be on the dawn side of the magnetosphere. During the third phase (also known as the Tail Science Phase) the apogees will be in the magnetotail. The fourth phase is called the Dusk Phase or Radiation Belt Science Phase, with all apogees on the dusk side. In the fifth and final phase, the apogees will shift to the sunward side (Dayside Science Phase). The satellite data will be combined with observations of the aurora from a network of 20 ground observatories across the North American continent. The THEMIS-B (THEMIS-P1) and THEMIS-C (THEMIS-P2) were repurposed to study the lunar environment in 2009. The spacecraft were renamed ARTEMIS (Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon’s Interaction with the Sun), with the P1 and P2 designations maintained.
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FANTOM stands for 'Functional Annotation of the Mammalian Genome' and is the name of an international research consortium organized by the RIKEN Omics Science Center. The FANTOM5 project aims to build a full understanding of transcriptional regulation in a human system by generating transcriptional regulatory networks that define every human cell type.