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Provides a web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. cBioPortal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface, combined with customized data storage, enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes.
DataSHIELD / Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual-levEL Databases
Allows the analysis of sensitive individual-level data from one study. DataSHIELD permits co-analysis of such data from several studies simultaneously without physically pooling them or disclosing any data. It can be applied to post-publication sensitive data analysis or text data analysis and permits to protect privacy data visualisation. The tool does not require the setup of substantial infrastructure. It allows the user to reduce data governance restrictions, and to reduce the time taken for co-analysis.
tranSMART-XNAT Connector
Consists of components for data capture, organisation and analysis. TranSMART-XNAT Connector organises data in a similar fashion as tranSMART and stores in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects’ clinical phenotypic and genotypic criteria. Development of the tranSMART-XNAT Connector addresses the need for management of very large datasets integrating broad range of phenotypic, genotype and laboratory data with imaging.
Allows scholarly recognition for data contributions. Dataverse can be used to specify if data requires special authorization for use due to their confidential or proprietary nature. It enables the data replication movement to spread to areas of science. The platform includes powerful search and advanced search features that allow one to find data by looking across all data sets, across those within a specific Dataverse Network, or only within a specific dataverse. It offers detailed customizable choices to dataverse owners for providing a hierarchical organization of available information.
InSilico DB
A collaborative platform that allows users to share genomic datasets. Dataset administrators can add/remove collaborators or groups of collaborators through a dedicated sharing interface. It is possible, as discussed in the 'Grouping and sub-grouping' section to create a new dataset by grouping samples from independent datasets. These newly generated datasets are private by default - that is, only the owner has access to them. Sharing preferences and the public status of the dataset can be changed by the owner. An owner of a dataset can make it public to the InSilico DB community or keep it private. A private dataset can be shared with collaborators who can be given read-only or read-and-write permissions. A user who has read-and-write permissions on a dataset can edit its sharing preferences.
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Hosts data and software tools associated with articles in GigaScience, and also a subset of data sets that is not associated with the journal. GigaDB is a database where a data set is defined as a group of files related to and support an article or study. The scope covers “omics” type data, the fields of high-throughput biology serviced by large public repositories, more difficult to-access data (imaging, neuroscience, ecolog, etc.) as well as software used to analyze large-scale data sets.
G-DOC / Georgetown Database of Cancer
Contains molecular and clinical data from thousands of patients and cell lines, along with tools for analysis and data visualization. G-DOC Plus enables the integrative analysis of multiple data types to understand disease mechanisms. The platform has three overlapping entry points for the user based on their interests: 1) Personalized Medicine, 2) Translational Research, and 3) Population Genetics. All data derives from studies on topics such as breast cancer, wound healing, or even 1,000 Genomes.
SBDG / Structural Biology Data Grid
Allows users to discover, download and deposit large structural biology datasets. SBDG is a flexible data publication system that allows deposition of a variety of large primary datasets. The database collection is limited to datasets that support journal publications, referred to as primary data. Datasets are stored as sets of experimental metadata (experimenters, sample, collection facility) and associated files and directories comprising the data of interest. SBDG can facilitate integration of the Data Grid with regional projects and preservation of primary diffraction datasets.
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