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Found 39 result(s)
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The Autism Chromosome Rearrangement Database is a collection of hand curated breakpoints and other genomic features, related to autism, taken from publicly available literature: databases and unpublished data.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.
LifeMap Discovery® is a compendium of embryonic development for stem cell research and regenerative medicine, constructed by integrating extensive molecular, cellular, anatomical and medical data curated from scientific literature and high-throughput data sources.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
SRUC is currently on a transformational journey as we move towards becoming a unique, market-led and mission diverse 21st Century rural university, driving the future needs of a dynamic, innovative and competitive rural sector in Scotland, and working with our collaborators and partners worldwide to solve the biggest global agrifood challenges. Our researchers already carry out strategic and applied research on global and local food security issues, and actively support the translation of research results into practice. Our research ethos is strongly collaborative, and we have a long history of industrial, NGO and academic partnerships locally and internationally. As well as having longstanding disciplinary strengths in several key areas, we actively promote interdisciplinary research, especially linking natural and social sciences. We have a particular interest in research that helps inform policy, with Scottish and UK Government rural affairs and environment departments and the EU as key research clients.
The IMSR is a searchable online database of mouse strains, stocks, and mutant ES cell lines available worldwide, including inbred, mutant, and genetically engineered strains. The goal of the IMSR is to assist the international scientific community in locating and obtaining mouse resources for research. Note that the data content found in the IMSR is as supplied by strain repository holders. For each strain or cell line listed in the IMSR, users can obtain information about: Where that resource is available (Repository Site); What state(s) the resource is available as (e.g. live, cryopreserved embryo or germplasm, ES cells); Links to descriptive information about a strain or ES cell line; Links to mutant alleles carried by a strain or ES cell line; Links for ordering a strain or ES cell line from a Repository; Links for contacting the Repository to send a query
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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.
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
We are working on a new version of ALFRED web interface. The current web interface will not be available from December 15th, 2023. There will be a period where a public web interface is not available for viewing ALFRED data. Expected date for the deployment of the new ALFRED web interface with minimum functions is March 1st, 2024 --------------------------------------------- ALFRED is a free, web-accessible, curated compilation of allele frequency data on DNA sequence polymorphisms in anthropologically defined human populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation.
Content type(s)
CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
Reactome is a manually curated, peer-reviewed pathway database, annotated by expert biologists and cross-referenced to bioinformatics databases. Its aim is to share information in the visual representations of biological pathways in a computationally accessible format. Pathway annotations are authored by expert biologists, in collaboration with Reactome editorial staff and cross-referenced to many bioinformatics databases. These include NCBI Gene, Ensembl and UniProt databases, the UCSC and HapMap Genome Browsers, the KEGG Compound and ChEBI small molecule databases, PubMed, and Gene Ontology.
BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
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.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
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The Human Genetic Variation Database (HGVD) aims to provide a central resource to archive and display Japanese genetic variation and association between the variation and transcription level of genes. The database currently contains genetic variations determined by exome sequencing of 1,208 individuals and genotyping data of common variations obtained from a cohort of 3,248 individuals.
The 1000 Genomes Project is an international collaboration to produce an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts. This resource will support genome-wide association studies and other medical research studies. The genomes of about 2500 unidentified people from about 25 populations around the world will be sequenced using next-generation sequencing technologies. The results of the study will be freely and publicly accessible to researchers worldwide. The International Genome Sample Resource (IGSR) has been established at EMBL-EBI to continue supporting data generated by the 1000 Genomes Project, supplemented with new data and new analysis.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
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.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.