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Found 6 result(s)
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
GENCODE is a scientific project in genome research and part of the ENCODE (ENCyclopedia Of DNA Elements) scale-up project. The GENCODE consortium was initially formed as part of the pilot phase of the ENCODE project to identify and map all protein-coding genes within the ENCODE regions (approx. 1% of Human genome). Given the initial success of the project, GENCODE now aims to build an “Encyclopedia of genes and genes variants” by identifying all gene features in the human and mouse genome using a combination of computational analysis, manual annotation, and experimental validation, and annotating all evidence-based gene features in the entire human genome at a high accuracy.
EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
EMAGE (e-Mouse Atlas of Gene Expression) is an online biological database of gene expression data in the developing mouse (Mus musculus) embryo. The data held in EMAGE is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. EMAGE is a freely available web-based resource funded by the Medical Research Council (UK) and based at the MRC Human Genetics Unit in the Institute of Genetics and Molecular Medicine, Edinburgh, UK.
CLARIN-UK is a consortium of centres of expertise involved in research and resource creation involving digital language data and tools. The consortium includes the national library, and academic departments and university centres in linguistics, languages, literature and computer science.
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. PRIDE encourages and welcomes direct user submissions of mass spectrometry data to be published in peer-reviewed publications.