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Found 23 result(s)
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>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed.
The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative.
CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month.
As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive.
The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there.
The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<<
The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects.
Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.
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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.
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eLMSG (eLibrary of Microbial Systematics and Genomics) is a web microbial library that integrates not only taxonomic information, but also genomic information and phenotypic information (including morphology, physiology, biochemistry and enzymology). The taxonomic system of eLMSG is manually curated and composed of all validly and some effectively published taxa. For each taxon, the Latin name, taxon ID (NCBI taxonomy), etymology, rank, lineage, the dates of effective and/or valid publication, feature descriptions, nomenclature type and references for the proposal and emendations during the history of the taxon are presented. Besides these data, the species taxa contain information about 16S rRNA gene and/or genome sequences. All publicly available genome data of each type species including both type and non-type strains were collected, and if needed, re-annotated using the standardized analysis pipeline. Furthermore, pan-genomic data analyses were conducted for species with ≥5 genome sequences available. Finally, for all type species, taxonomically relevant phenotypic data were extracted and curated from literatures, which were further indexed into eLMSG as searchable and analyzable data records. Taken together, eLMSG is a comprehensive web platform for studying mi- crobial systematics and genomics, potentially useful for better understanding microbial taxonomy, natural evolutionary processes and ecological relationships.
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A small genotype data repository containing data used in recent papers from the Estonian Biocentre. Most of the data pertains to human population genetics. PDF files of the papers are also freely available.
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Born of the desire to systematize analyses from The Cancer Genome Atlas pilot and scale their execution to the dozens of remaining diseases to be studied, GDAC Firehose now sits atop terabytes of analysis-ready TCGA data and reliably executes thousands of pipelines per month. More information: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/
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<<<!!!<<< The PEP database (TBestDB)--Defunct as of 2017-04 >>>!!!>>>
https://megasun.bch.umontreal.ca/pepdb/pepdb.html
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<<<!!!<<< This repository is no longer available. >>>!!!>>>
NetPath is currently one of the largest open-source repository of human signaling pathways that is all set to become a community standard to meet the challenges in functional genomics and systems biology. Signaling networks are the key to deciphering many of the complex networks that govern the machinery inside the cell. Several signaling molecules play an important role in disease processes that are a direct result of their altered functioning and are now recognized as potential therapeutic targets. Understanding how to restore the proper functioning of these pathways that have become deregulated in disease, is needed for accelerating biomedical research. This resource is aimed at demystifying the biological pathways and highlights the key relationships and connections between them. Apart from this, pathways provide a way of reducing the dimensionality of high throughput data, by grouping thousands of genes, proteins and metabolites at functional level into just several hundreds of pathways for an experiment. Identifying the active pathways that differ between two conditions can have more explanatory power than just a simple list of differentially expressed genes and proteins.
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IUBio Archive is an archive of biology data and software. The archive includes items to browse, search and fetch public software, molecular data, biology news and documents.
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PathCards is an integrated database of human biological pathways and their annotations. Human pathways were clustered into SuperPaths based on gene content similarity. Each PathCard provides information on one SuperPath which represents one or more human pathways.
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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.
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OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.
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The goals of FMGP are to:
(i) sequence complete mitochondrial genomes from all major fungal lineages,
(ii) infer a robust fungal phylogeny,
(iii) define the origin of the fungi, their protistan ancestors, and their specific phylogenetic link to the animals,
(iv) investigate mitochondrial gene expression, introns, RNAse P RNA structures, mobile elements.
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<<<!!!<<< The data are no longer accessible. Message: Adobe Flash Player is no longer supported >>>!!!>>>
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FANTOM stands for 'Functional Annotation of the Mammalian Genome' and is the name of an international research consortium organized by the RIKEN Omics Science Center. The FANTOM5 project aims to build a full understanding of transcriptional regulation in a human system by generating transcriptional regulatory networks that define every human cell type.
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<<<!!!<<< DTU Bioinformatics was closed on 31 December 2018 as part of a reorganization at DTU >>>!!!>>>
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The Allen Brain Atlas provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate
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The Entrez Protein Clusters database contains annotation information, publications, structures and analysis tools for related protein sequences encoded by complete genomes. The data available in the Protein Clusters Database is generated from prokaryotic genomic studies and is intended to assist researchers studying micro-organism evolution as well as other biological sciences. Available genomes include plants and viruses as well as organelles and microbial genomes.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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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).
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MetaCyc is a curated database of experimentally elucidated metabolic pathways from all domains of life.
MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated metabolites, reactions, enzymes, and genes. The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway.
MetaCyc applications include: Online encyclopedia of metabolism, Prediction of metabolic pathways in sequenced genomes, Support metabolic engineering via enzyme database, Metabolite database aids. metabolomics research.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
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ALSPAC is a longitudinal birth cohort study which enrolled pregnant women who were resident in one of three Bristol-based health districts in the former County of Avon with an expected delivery date between 1st April 1991 and 31st December 1992. Around 14,000 pregnant women were initially recruited. Detailed information has been collected on these women, their partners and subsequent children using self-completion questionnaires, data extraction from medical notes, linkage to routine information systems and from hands-on research clinics.
Additional cohorts of participants have since been enrolled in their own right including fathers, siblings, children of the children and grandparents of the children.
Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee (IRB00003312) and Local Research Ethics.
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<<<!!!<<< 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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To the extent possible under law,
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- Cite this service: re3data.org - Registry of Research Data Repositories. https://doi.org/10.17616/R3D last accessed: 2024-06-25
