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Found 20 result(s)
Complete Genomics provides free public access to a variety of whole human genome data sets generated from Complete Genomics’ sequencing service. The research community can explore and familiarize themselves with the quality of these data sets, review the data formats provided from our sequencing service, and augment their own research with additional summaries of genomic variation across a panel of diverse individuals. The quality of these data sets is representative of what a customer can expect to receive for their own samples. This public genome repository comprises genome results from both our Standard Sequencing Service (69 standard, non-diseased samples) and the Cancer Sequencing Service (two matched tumor and normal sample pairs). In March 2013 Complete Genomics was acquired by BGI-Shenzhen , the world’s largest genomics services company. BGI is a company headquartered in Shenzhen, China that provides comprehensive sequencing and bioinformatics services for commercial science, medical, agricultural and environmental applications. Complete Genomics is now focused on building a new generation of high-throughput sequencing technology and developing new and exciting research, clinical and consumer applications.
GOLD is currently the largest repository for genome project information world-wide. The accurate and efficient genome project tracking is a vital criterion for launching new genome sequencing projects, and for avoiding significant overlap between various sequencing efforts and centers.
Database and knowledgebase of authenticated microbial genomics data with full data provenance to physical materials held within American Type Culture Collection's (ATCC) biorepository and culture collections. Data includes whole genome sequencing data for bacterial, viral and fungal strains at ATCC, their genome assemblies, metadata, drug susceptibility data, and more. All data is freely available for non-commercial research use only (RUO) applications via the web portal interface or via a REST-API. The goal is to provide the research community with provenance information and authentication between the biological source materials and reference genome assemblies derived from them.
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and gene expression data collected by or in collaboration with researchers at the University of Wisconsin - Madison. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments.
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The Organelle Genome Megasequencing Program (OGMP) provides mitochondrial, chloroplast, and mitochondrial plasmid genome data. OGMP tools allow direct comparison of OGMP and NCBI validated records. Includes GOBASE, a taxonomically broad organelle genome database that organizes and integrates diverse data related to mitochondria and chloroplasts.
The Progenetix database provides an overview of copy number abnormalities in human cancer from currently 32548 array and chromosomal Comparative Genomic Hybridization (CGH) experiments, as well as Whole Genome or Whole Exome Sequencing (WGS, WES) studies. The cancer profile data in Progenetix was curated from 1031 articles and represents 366 different cancer types, according to the International classification of Diseases in Oncology (ICD-O).
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.
The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to search, download, and analyze data sets generated by TCGA. It contains clinical information, genomic characterization data, and high level sequence analysis of the tumor genomes. The Data Coordinating Center (DCC) is the central provider of TCGA data. The DCC standardizes data formats and validates submitted data.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
The European Bioinformatics Institute (EBI) has a long-standing mission to collect, organise and make available databases for biomolecular science. It makes available a collection of databases along with tools to search, download and analyse their content. These databases include DNA and protein sequences and structures, genome annotation, gene expression information, molecular interactions and pathways. Connected to these are linking and descriptive data resources such as protein motifs, ontologies and many others. In many of these efforts, the EBI is a European node in global data-sharing agreements involving, for example, the USA and Japan.
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.
The European Genome-phenome Archive (EGA) is designed to be a repository for all types of sequence and genotype experiments, including case-control, population, and family studies. We will include SNP and CNV genotypes from array based methods and genotyping done with re-sequencing methods. The EGA will serve as a permanent archive that will archive several levels of data including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters. We are developing data mining and access tools for the database. For controlled access data, the EGA will provide the necessary security required to control access, and maintain patient confidentiality, while providing access to those researchers and clinicians authorised to view the data. In all cases, data access decisions will be made by the appropriate data access-granting organisation (DAO) and not by the EGA. The DAO will normally be the same organisation that approved and monitored the initial study protocol or a designate of this approving organisation. The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies
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>>>!!! <<< 2021-09-01: repository is offline >>>!!!<<< Background: Many studies have been conducted to detect quantitative trait loci (QTL) in dairy cattle. However, these studies are diverse in terms of their differing resource populations, marker maps, phenotypes, etc, and one of the challenges is to be able to synthesise this diverse information. This web page has been constructed to provide an accessible database of studies, providing a summary of each study, facilitating an easier comparison across studies. However, it also highlights the need for uniform reporting of results of studies, to facilitate more direct comparisons being made. Description: Studies recorded in this database include complete and partial genome scans, single chromosome scans, as well as fine mapping studies, and contain all known reports that were published in peer-reviewed journals and readily available conference proceedings, initially up to April 2005. However, this data base is being added to, as indicated by the last web update. Note that some duplication of results will occur, in that there may be a number of reports on the same resource population, but utilising different marker densities or different statistical methodologies. The traits recorded in this map are milk yield, milk composition (protein yield, protein %, fat yield, fat %), and somatic cell score (SCS).
The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.