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Found 3 result(s)

The Monarch Initiative

Monarch Initiative

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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.

eFish

Genomic Database Repository

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The project aims to examine and index the genomic diversity through the generation of complete mitochondrial and nuclear genome sequences of sharks and rays of the Pacific Rim. There is a huge diversity of elasmobranch fishes in this region, but many species are under threat because of poor management and conservation measures in many countries. It is absolutely critical that species’ identities are correct for conservation and fisheries management purposes. This project will provide this clarity of identity for both charismatic and commercially important species through the inclusion of ‘genetypes’ (ie., BioVouchers) and the application of genetic tools that utilize whole mitochondrial and nuclear genome sequences.

ALSoD

ALS Online Database

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ALSoD is a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.