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Found 12 result(s)
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Androgen Receptor Gene Mutations Database is for all who are interested in mutations of the Androgen Receptor Gene. In light of the difficulty in getting new AR mutations published the curator will now accept new mutations that have not been published, provided that it is from a reputable research or clinical laboratory. The curator also strongly suggests that where possible, particularly in the case of new unique mutations that an attempt be made to at least confirm the pathogenicity of the putatative mutation, by showing that the mutation when transfected into a suitable expression system produces a mutant androgen receptor protein.
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The Cystic Fibrosis Mutation Database (CFTR1) was initiated by the Cystic Fibrosis Genetic Analysis Consortium in 1989 to increase and facilitate communications among CF researchers, and is maintained by the Cystic Fibrosis Centre at the Hospital for Sick Children in Toronto. The specific aim of the database is to provide up to date information about individual mutations in the CFTR gene. In a major upgrade in 2010, all known CFTR mutations and sequence variants have been converted to the standard nomenclature recommended by the Human Genome Variation Society.
A curated database of mutations and polymorphisms associated with Lafora Progressive Myoclonus Epilepsy. The Lafora progressive myoclonus epilepsy mutation and polymorphism database is a collection of hand curated mutation and polymorphism data for the EPM2A and EPM2B (NHLRC1) from publicly available literature: databases and unpublished data. The database is continuously updated with information from in-house experimental data as well as data from published research studies.
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>>>!!!<<< The repository is no longer available. >>>!!!<<< Indian Genetic Disease Database (IGDD) is an initiative of CSIR Indian Institute of Chemical Biology. It is supported by Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT) of India. The Indian people represent one-sixth of the world population and consists of a ethnically, geographically, and genetically diverse population. In some communities the ratio of genetic disorder is relatively high due to consanguineous marriage practiced in the community. This database has been created to keep track of mutations in the causal genes for genetic diseases common in India and help the physicians, geneticists, and other professionals retrieve and use the information for the benefit of the public. The database includes scientific information about these genetic diseases and disabilities, but also statistical information about these diseases in today's society. Data is categorized by body part affected and then by title of the disease.
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Oral Cancer Gene Database is an initiative of the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai. The present database, version II, consists of 374 genes. It is developed as a user friendly site that would provide the scientist, information and external links from one place. The database is accessed through a list of all genes, and Keyword Search using gene name or gene symbol, chromosomal location, CGH (in %), and molecular weight. Interaction Network shows the interaction between genes for particular biological processes and molecular functions.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> Message since 2018-06: This virtual host is being reconstructed.
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.