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Found 116 result(s)
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SISSA Open Data is the Sissa repository for the research data managment. It is an institutional repository that captures, stores, preserves, and redistributes the data of the SISSA scientific community in digital form. SISSA Open Data is managed by the SISSA Library as a service to the SISSA scientific community.
IMGT/GENE-DB is the IMGT genome database for IG and TR genes from human, mouse and other vertebrates. IMGT/GENE-DB provides a full characterization of the genes and of their alleles: IMGT gene name and definition, chromosomal localization, number of alleles, and for each allele, the IMGT allele functionality, and the IMGT reference sequences and other sequences from the literature. IMGT/GENE-DB allele reference sequences are available in FASTA format (nucleotide and amino acid sequences with IMGT gaps according to the IMGT unique numbering, or without gaps).
The Barcode of Life Data Systems (BOLD) provides DNA barcode data. BOLD's online workbench supports data validation, annotation, and publication for specimen, distributional, and molecular data. The platform consists of four main modules: a data portal, a database of barcode clusters, an educational portal, and a data collection workbench. BOLD is the go-to site for DNA-based identification. As the central informatics platform for DNA barcoding, BOLD plays a crucial role in assimilating and organizing data gathered by the international barcode research community. Two iBOL (International Barcode of Life) Working Groups are supporting the ongoing development of BOLD.
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A genome database for the genus Piroplasma. PiroplasmaDB is a member of pathogen-databases that are housed under the NIAID-funded EuPathDB Bioinformatics Resource Center (BRC) umbrella.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
BioGPS is a gene portal built with two guiding principles in mind -- customizability and extensibility. It is a complete resource for learning about gene and protein function. A free extensible and customizable gene annotation portal, a complete resource for learning about gene and protein function.
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Database for identification and cataloguing of group II introns. All bacterial introns listed are full-length and appear to be functional, based on intron RNA and IEP characteristics. The database names the full-length introns, and provides information on their boundaries, host genes, and secondary structures. In addition, the website provides tools for analysis that may be useful to researchers who encounter group II introns in DNA sequences. Intron data can be downloaded in FASTA format.
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.
The UniProt Reference Clusters (UniRef) provide clustered sets of sequences from the UniProt Knowledgebase (including isoforms) and selected UniParc records in order to obtain complete coverage of the sequence space at several resolutions while hiding redundant sequences (but not their descriptions) from view.
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>>>!!!<<<As stated 2017-05-23 Cancer GEnome Mine is no longer available >>>!!!<<< Cancer GEnome Mine is a public database for storing clinical information about tumor samples and microarray data, with emphasis on array comparative genomic hybridization (aCGH) and data mining of gene copy number changes.
The miRBase database is a searchable database of published miRNA sequences and annotation. Each entry in the miRBase Sequence database represents a predicted hairpin portion of a miRNA transcript (termed mir in the database), with information on the location and sequence of the mature miRNA sequence (termed miR). Both hairpin and mature sequences are available for searching and browsing, and entries can also be retrieved by name, keyword, references and annotation. All sequence and annotation data are also available for download. The miRBase Registry provides miRNA gene hunters with unique names for novel miRNA genes prior to publication of results.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
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The objective of this project is to generate the most comprehensive description of human chromosome 7 to facilitate biological discovery, disease gene research and medical genetic applications. In our vision, the DNA sequence of chromosome 7 should be made available in a user-friendly manner having every biological and medically relevant feature annotated along its length. We have established this website and database as one step towards this goal. In addition to being a primary data source we foresee this site serving as a "weighing station" for testing community ideas and information to produce highly curated data to be submitted to other databases such as NCBI, Ensembl, and UCSC. Therefore, any useful data submitted to us will be curated and shown in this database.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.